Qian Li

Jia Li

Sha Song

Wujun Chen

Xin Shen
email: shenxin@cppqd.com

Suming M Li
email: suming.li@umontpellier.fr

Dongming Xing

Nanoparticle-mediated tumor vaccines for personalized therapy: preparing tumor antigens in vivo or ex vivo?

Keywords: tumor vaccine, antigen release, antigen delivery, personalized therapy, nanoparticles

Tumor vaccine, focusing on tailoring individual tumor antigens, has gained much attention in personalized tumor therapy. Recently, breakthroughs have been made in the development of tumor vaccines thanks to the progress in nanotechnology. We will summarize nanoparticle-mediated tumor vaccines for personalized therapy in this review. ROS/heat generating nanoparticles and molecules could induce immunogenic cell death and tumor antigen release in vivo. This strategy often includes chemotherapy, radiotherapy, photodynamic therapy, photothermal therapy, magneto-thermal therapy, etc. On the other hand, ex vivo technologies have been applied for processing of tumor cells/tissues to form effective tumor antigens, in which nanotechnology have shown very good prospects in delivering tumor antigens. In in vivo and ex vivo strategies, nanotechnology also could improve immune effect through enhancing uptake by targeting cells, reducing therapeutic drugs/agents, further encapsulating immuno-modulatory molecules or combining with other therapy treatments. Thus, therapeutic vaccines based on nanoparticles have the potential to enhance immune response and reduce side effects.

Introduction

As every tumor has its own unique composition of mutations with only a small fraction shared between patients, there is a huge demand in developing personalized therapy. 1 Therapeutic tumor vaccines represent a viable option for personalized therapy that aims to treat late stage disease by using a patient's own immune system. Several therapeutic tumor vaccine strategies and formulations have been evaluated in recent years in different tumor settings involving thousands of tumor patients. 2,3 However, therapeutic tumor vaccines have not made proportionate clinical effect. The only FDA-approved tumor vaccine, Provenge ® showed a limited 4.5-month improvement in overall survival compared to the placebo. Nevertheless, this major breakthrough not only provides a new treatment modality for tumor management, but also paves the way for rationally designing and optimizing future vaccines with improved anti-tumor efficacy. Compared with the other types of tumor treatments, tumor vaccine therapies are considered to be a type of specific, safe, and welltolerated tumor treatment, and they have the potential to avoid drug resistance and obtain durable treatment responses due to the long-term immunologic memory. 4 The limited efficacy could be described to the low specificity of target tumor antigens in the vaccine formulation. Tumor antigens need to be sufficiently distinct from self-antigens to break the immunological tolerance that physiologically blocks undesired auto-immune reactivity against normal cells. Thus, preparing appropriate tumor antigens is one of the central factors in the development of tumor vaccines. [START_REF] Valilou | Tumor Antigens[END_REF] Ex vivo technologies have been used to look for effective tumor antigens for a long period, and several strategies including tumor lysate based vaccine, [START_REF] Shi | [END_REF]7 tumor cell membrane based vaccine 8,9 and neoantigen 10 have shown the advantage of personalization. Moreover, tumor killing strategies have been introduced into tumor vaccines for inducing tumor antigen release in vivo, and these strategies usually include photodynamic therapy, chemotherapy, radiotherapy, hyperthermia, etc. [11][12][13] However, these treatments suffer from limited induction of immune response for different reasons such as un-stability of tumor cell contents, poor dendritic cells (DCs) uptake of tumor antigens, inefficient antigen cross-presentation. [START_REF] Shi | [END_REF][14][15][16] The use of smart nanosystems represents an opportunity for improving immune responses.

Generation of anti-cancer immune response consists in a number of key steps as follows 17 : Introduce tumor antigens, antigen presenting cells (APCs) present tumor antigens, activated APCs present tumor antigens to T cells, activated effector T cells kill tumor cells releasing epitope spreading. As tumor antigen plays the key role in tumor vaccines, various nanoparticles have been applied in tumor antigen preparation (Figure 1). Nanoparticles with the function of generating ROS/heats could induce antigen release in vivo, [18][19][20] while nano-delivery systems demonstrate very good prospects in processing and delivering tumor antigens ex vivo. 21,22 In in vivo and ex vivo strategies, nanotechnology also could improve immune effect through enhancing uptake by targeting cells, reducing therapeutic drugs/agents, further encapsulating immuno-modulatory molecules or combining with other therapy treatments. In this review, we will summarize the application of nanoparticles for improving the efficiency of the tumor vaccines.

Inducing tumor antigens in vivo

In situ tumor vaccine, which could generate tumor vaccines in vivo, is a newly defined form of tumor therapeutic method based on immunogenic cell death (ICD). 13,19,23 Molecules essential for the induction of ICD are called damage-associated molecular patterns (DAMPs). 24 DAMPs have the ability to recruit APCs and stimulate optimal antigen presentation to T cells. In situ tumor vaccine also triggers the release of tumor antigens including neoantigens derived from idiosyncratic mutations. [25][26][27] DAMPs secreting and neoantigen releasing provide in situ tumor vaccines the ability to generate systemic anti-tumor adaptive immune responses. The production of ROS and the resulting induction of endoplasmic reticulum (ER) stress are vital for the intracellular trafficking and subsequent surface/extracellular emission of DAMPs/danger signals. 12,28 Generation of ROS is related to most of the currently known ICD inducers such as chemotherapy, radiotherapy, photodynamic therapy (PDT), photothermal therapy (PTT) and magneto-thermal therapy (MTT), as shown in Figure 2. Photodynamic therapy efficiently generates ROS through PDT action, 29 while others generate ROS through collateral pathways. 12,26,28 Beside ROS, the heat generated through the process of hyperthermia also could induce ER stress. A small increase in temperature can cause protein unfolding, entanglement and aggregation leading to an imbalance in proteostasis. This can result in increased degradation of aggregated/misfolded proteins, and cellular effects such as ER stress, cellular apoptosis and necrosis. 30,31 Figure 2. Schematic depiction of in vivo strategies inducing ER stress and releasing DAMPs

Photodynamic therapy

Photodynamic therapy (PDT) is a clinically used, minimally invasive therapeutic treatment on neoplastic pathologic tissues. PDT agents (also named photosensitizers) absorb visible non-thermal light within the phototherapeutic window (λ> 600 nm) forming excited state of photosensitizer, and generate ROS through Type I and/or Type II photochemistry. 32,33 Although PDT has not yet become the mainstream of tumor intervention mainly due to its insufficient therapeutic efficacy and limited light penetration for deep tumor tissues, 34,[START_REF] Castano | Proc. Natl. Acad. Sci. U S A[END_REF] PDT has returned to the spotlight for its noticeable immune activity. ICD-associated immunogenicity can be evoked through ROS produced ER stress. [START_REF] Li | [END_REF] The ROS production and ER stress are crucial for instigation of the danger signalling pathways responsible for the trafficking and emission of DAMPs. Compared to chemotherapy and radiotherapy, PDT generates ROS more directly and does not cause severe side effects such as leucopenia and gastrointestinal reactions. 37,38 Thus, PDT can induce tumor cells to produce more DAMPs and are more effective at inducing ICD. 28 Antigen releasing also enhances anti-tumor immune responses. 39 The released DAMPs and tumor antigen signal APCs maturation accompanied by infiltration of inflammatory cells. These tissue changes further stimulate the inflammatory cells to release proinflammatory cytokines such as IL-1β, TNF-α, IL-6, IL-10, etc. 40,41 The infiltration of inflammatory cells and production of proinflammatory cytokines supply powerful tools in eliciting in situ tumors, but as importantly, it has the potential to kill the residual or metastatic tumor cells.

In an effort to enhance the effectiveness of antitumor PDT, many studies have been conducted to develop photosensitizers with longer wavelength absorption, 42 solve the problem of tissue hypoxia 43,44 and selective photosensitizer delivery to target cells 45,46 . These approaches not only improved the efficiency of directly killing tumors, but also facilitate the antitumor immune response following PDT. Several molecules generating ROS have been proved powerful PDT agents in tumor immune therapy. These molecules include chlorin e6 (Ce 6), hypericin, silicon(IV) phthalocyanine, zinc(II) phthalocyanine, pyropheophorbide-a, etc. 12,43,47 For example, Chen et al. reported a Ce6 encapsulated hybrid protein oxygen nanocarrier (C@HPOC) made up from human serum albumin and hemoglobin (Figure 3a). 43 The nanocarrier realized the tumor-targeted co-delivery of photosensitizer and oxygen, which remarkably relieved tumor hypoxia. C@HPOC showed more efficient PDT and enhanced infiltration of CD8 + T cells in tumors. Moreover, oxygen-boosted PDT of C@HPOC induced immunogenic cell death, with the release of DAMPs to activate dendritic cells, T lymphocytes, and natural killer cells in vivo. Notably, C@HPOC-mediated immunogenic PDT could destroy primary tumors and effectively suppress distant tumors and lung metastasis in metastatic triple-negative breast tumor model.

Combination therapy that could better balance immune activation and suppressive signals presents great potential in tumor immunotherapy. Yang et al. designed a smart nanovesicle with ICD inducing ability as synergist for photosensetizers. 47 The smart nanovesicles were selfassembled from a pH-responsive block copolymer of polyethylene glycol with a cationic polypeptide, and co-loaded with 2-(1-hexyloxyethyl)-2-devinyl pyropheophorbide-a (HPPH) and indoximod. ICD was induced through HPPH-mediated PDT and preapoptotic exposure of calreticulin caused by nanovesicles. Indoximod modulated tumor microenvironment via enhancing P-S6K phosphorylation for CD 8+ T cell development. This work exploited the nanocarrier's potential to induce ICD for the host's immunity activation. The "all-in-one" smart nanovesicles allow the design of multifunctional materials to improve tumor immunotherapy efficacy. Nanomaterials, which could generate ROS under light, also aroused much attention in PDTgenerated vaccine. Nanoparticles generating ROS include black phosphorus quantum dots (BPQDs), gold nanocages, benzoporphyrin-based metal-organic frameworks (TBP-MOF), etc. 42,48,49 3b). 49 CpG oligodeoxynucleotides (CpG ODNs) was loaded as immuno-adjuvant in the cavity of the BPNVs. Upon NIR laser irradiation, high levels of ROS are generated from BPNVs to trigger the release of BPQD and CpG into deep tumors. The potent ICD effect and local accumulation of CpG induced an antitumor immune response, which also effectively inhibited distant tumor growth and lung metastasis.

The Fenton reaction, which converts hydrogen peroxide to reactive oxygen radicals, has attracted much interestin enhancing PDT performance. It usually utilizes small amounts of Fe 2+ and Fentonlike reaction utilizes Cu + and its complexes acting as a catalyst. Recently, these catalysts have been introduced into PDT-based immune-therapy. For example, Wang et al. designed an ultra small nanoagent (3.1 ± 0.4 nm) fabricated from PEG modified Cu2-xSe nanoparticles, β-cyclodextrin, and Ce6 under ambient conditions. 50 The resultant nanoplatform showed excellent PDT performance through Fenton-like Haber-Weiss catalyst under near-infrared irradiation. The antitumor immune responses against the metastasis of breast tumor were robustly evoked through eliciting ICD to release DAMPs and induced proinflammatory M1-macrophages polarization. Thereby the nanoparticle-based nanoplatform offers a promising way to prevent metastatic breast tumor via immunogenic effects through its excellent PDT performance.

Chemotherapy

Conventional chemotherapy relies on direct elimination of tumor cells. As scientific research progress, role of chemotherapy in eliciting anti-tumor immune responses has aroused much attention.

Subsequent molecular studies demonstrated that the concomitant production of ROS during chemotherapy is crucial for instigation of ER stress and emission of DAMPs. 12,53 Several chemodrugs have been shown to undergo ICD and generate different DAMPs. Such inducers primarily cause tumor cell death by acting on DNA replication/repair proteins or certain cytosolic proteins.

Chemo-drugs acted on DNA replication/repair proteins include anthracyclines (doxorubicin, etc.), mitoxantrone, oxaliplatin, cyclophosphamide, [54][55][56][57][58] while bortezomib mainly acted on cytoplasmic proteins. 59 Accordingly, DNA replication/repair proteins and cytoplasmic proteins represent the site of "focused" effects for chemo-drugs, while the ER represents the site of "collateral" effects. They induce cell death are not directly associated with the ER, but ICD-associated danger signalling is through collateral ER stress effects.

Chemotherapy induced antitumor immune responses was dosage-dependent. A high dose of chemotherapeutic drug would cause side effects such as leukopenia. However, a low dosage of chemotherapeutic drug is inefficient to induce immune response. In order to enhance immune response, nanotechnology has been introduced into chemotherapy-based tumor vaccines. On the one hand, nanoparticle-based drug delivery systems (DDSs) can advantageously enhance therapeutic efficacy by better penetration and controlled release of active ingredients at the target site, producing more serum stability and pharmacokinetics. On the other hand, the DDSs can further encapsulate immuno-modulatory molecules or combine with other therapy treatments.

Encapsulating chemotherapeutic drugs into DDSs thus offers a promising way to enhance immune effects.

Materials for preparing nano-carriers usually include organic DDSs and inorganic DDSs. Organic DDSs are usually biodegradable, which includes dendrimers, liposome, micelles, and polymer nanoparticles. 60,61 These DDSs are able to encapsulate various chemotherapeutic drugs, and give them advantages such as prolonged circulation time in the body, specific targeting and improved drug solubility. 62 Some of these organic DDSs have been used in tumor immune therapy. For example, Duan et al. prepared nanoscale coordination polymer (NCP) core-shell particles to encapsulate oxaliplatin (OxPt) and dihydroartemisinin (DHA) prodrugs (Figure 3c). 51 OxPt and DHA have strong synergy in ROS generation activity. The combined ROS generation is harnessed for immune activation to synergize with an anti-PD-L1 antibody for the treatment of murine colorectal tumours. OxPt/DHA directly converted treated tumours into an in situ vaccine through inducing calreticulin (CRT) exposure and HMGB-1 release, accompanied by recruiting antigenpresenting DCs and macrophages, facilitating cancer cell phagocytosis, enhancing antigen presentation, and finally increasing intra-tumoural infiltration of CD8 + T cells to significantly potentiate checkpoint. The favourable biodistribution and tumor uptake of NCPs allow for repeated dosing to afford 100% tumor eradication and generating long-term anti-tumor immunity.

Inorganic materials, such as calcium carbonate (CaCO3), calcium phosphate (Ca(H2PO4)2), tri calcium phosphate (Ca3(PO4)2), hydroxy apatite (Ca5(PO4)3OH), calcium peroxide (CaO2), colloidal gold, silicon, iron oxide and layered double hydroxide have been applied in modern pharmaceutical and medication areas. 63,64 Inorganic nanoparticles have been widely investigated in the field of drug delivery due to their controllable size, ease of preparation, simple functionalization, and high stability. Although studies investigating the mechanisms underlying the anti-tumor immune response to inorganic DDSs are in a nascent stage, some reports focus on their synthesis for inducing tumor vaccine. For example, Ruan et al. reported a combined therapeutic regimen based on gold nanoparticles-enabled chemotherapy and blockade of PD-L1 immune checkpoint. 65 The legumainresponsive gold nanoparticles could passively target the glioma site and enhanced accumulation of DOX and hydroxychloroquine (HCQ) at the glioma site. HCQ inhibited the DOX-induced cytoprotective autophagy, which resensitized glioma cells to DOX and inhibited the formation of autophagy-related vasculogenic mimicry by glioma stem cells. In vivo studies showed gold nanoparticles plus anti-PD-L1 antibody could further enhance antiglioma effect and efficiently prevent recurrence. The effectiveness of this strategy presents a potential avenue to develop a more effective and more personalized combination therapeutic regimen for glioma patients.

Radiotherapy

External beam-based cancer radiotherapy is a mainstream cancer treatment strategy that has been extensively used in clinic to treat 65-75% of local solid tumors at different stages. α-, β-and γ-rays from radioactive decays as well as X-rays have been applied locally onto tumors to kill cancer cells. However, radiotherapy is not able to inhibit the growth of distantly spreading tumors and limited by hypoxia inside solid tumors. Clinical treatment of tumors has found that some patients with disseminated tumor experienced systemic tumor regression after irradiation of a single tumor site.

Aside from causing tumor cell death by acting on DNA replication and repair proteins, 66 radiotherapy passing through living tissues could generate ROS. The effects of ROS are amplified by the interaction with ER stress pathways, resulting in the translocation of CRT to the cell surface (a DC "eat-me" signal) and the release of danger signals such as HMGB1 and ATP, which are essential for the promotion of CD8 + T cell anticancer responses. Primed CD8 + T cells contribute to subsequent residual tumor cell elimination in the tumor bed as well as nonirradiated tumor deposits at distant sites of disease. 13,28,67 Thus, combinational radio-immune oncotherapy could be considered as next generation cancer radiotherapy strategies.

Emerging applications of local radiotherapy has provided radiation oncologists with a method for converting malignant cells into endogenous anticancer vaccines. However, radiotherapy alone is unlikely to induce or sustain an immune response that is therapeutically useful based on clinical evidence. Nanomaterials could enhance immune response by priming with immune-modulators, tumor antigens or oxygen suppliers. 11,52,68 For example, Chen et al. reported poly(lactic-co-glycolic acid) (PLGA) based core-shell nanoparticles for tumor immunotherapy (Figure 3d). 52 R837 was loaded in the PLGA shell, while catalase with the ability to decompose H2O2 to O2 was loaded in the inner core. The formed nanoparticles could greatly enhance radiotherapy efficacy by relieving the tumor hypoxia and modulating the immune-suppressive tumor microenvironment. After combination with anti-CTLA4 (αCTLA4) checkpoint blockade, radiotherapy using R837 loaded PLGA nanoparticles showed excellent distant tumors control through an augmented abscopal effect.

Photothermal therapy

Photothermal therapy (PTT), a minimally invasive procedure using heat for attacking various types of tumor cells, has emerged as promising ICD inducer. PTT involves irradiation of lightabsorbing agents to an excited state under near-infrared (NIR) light in the tumor site where it releases vibrational energy (heat) and kills the tumor cells. Recently, PTT has shown the ability to generate antitumor immunological effects by producing tumor-specific/associate antigens and DMAPs from ablated tumor cell residues. It has been have demonstrated that the key event of hyperthermia appears to be protein denaturation and aggregation. 31 The correct structure and conformation of proteins is essential for their function in the cell. A small increase in temperature can cause protein unfolding, entanglement and aggregation, thus leading to an imbalance in proteostasis. 69 Increased degradation of aggregated/misfolded proteins could lead to ER stress, inactivation of protein synthesis, cell cycle arrest and inhibition of DNA repair processes. 31 Thus, tumor cells go through apoptosis or necrosis, resulting in release of tumor antigens and DAMPs. 70 Moreover, it has also been reported that hyperthermia promotes mannalian aerobic metabolism, induces oxidative stress and generates ROS rapidly. 30,71 ROS acting as danger signals induces immune response. Thus both heat and ROS generated in hyperthermia could contribute to ER stress and DAMPs release.

As an effective therapy for tumor, the PTT based immunotherapy has shown great promise. PTT agents ablate tumor cells with heat generated from the absorbed optical energy by light-absorbing agents that accumulate in the tumors. A number of PTT agents have been developed for immune therapy, including indocyanine green, prussian blue, gold nanoparticles, carbon nanotubes, grapheme oxide, CuS nanoparticles, and Bi2Se3 nanocage. 20,70,[72][73][74][75] Low penetration depth and limited immune stimulation are still the major obstacles for PTT. 72 To achieve a relatively harsh environment for efficient ablation of tumors, photothermal heating to temperatures over 50 ℃ is required, which will also damage normal tissues and induce intolerable pain to patients. Huang et al. reported the combination of mild PTT under 45 ℃ and anti-PD therapy. The authors prepared a lipid gel depot with a favorable property of thermally reversible gel-to-sol phase transition for encapsulation NIR photothermal agent new indocyanine green (IR-820) and PD-L1 antibody (αPD-L1) (Figure 4a). 74 Manually controlled NIR irradiation regulates the release of αPD-L1 and, more importantly, increases the recruitment of tumor-infiltrating lymphocytes and boosts T cell activity against tumors. In vivo antitumor studies on 4T1 and B16F10 models demonstrate that symbiotic mild photothermal-assisted immunotherapy is an effective and promising strategy for treating "cold" tumors.

Magneto-thermal therapy

Magneto-thermal therapy (MTT) is a favorable non-invasive technique for tumor therapy that selectively heats up tumor tissue by coupling alternating current magnetic fields to magnetic nanoparticles. Magnetic nanoparticles transform alternate current magnetic field energy into heat by different magnetic loss mechanisms, such as N´eel and Brownian losses. 77 Compared to traditional hyperthermia therapy or NIR laser-based hyperthermia, MTT has advantages of higher penetration ability of magnetic field in the tissues and enhanced accumulation of magnetic nanoparticles in the tumor via magnetic targeting strategy for tumor treatment. It has been reported that MTT could trigger an antitumor immune response mediated by both CD8 + and CD4 + T cells. This leads to elimination of both heat-treated primary tumors and unheated distant tumors and subsequent rechallenge rejection. 78,79 For most biomedical applications, magnetic nanoparticles are made from ferrimagnetic iron oxides. 80 Iron oxides nanoparticles are an attractive option as a base platform for developing constructs that enable potentially synergistic mechanisms of cancer cell killing to be more effective. 19 For example, Liu et al. propose a magneto-thermodynamic (MTD) approach by leveraging the dual action of the heating effect and reinforced ROS-related immunologic effect to efficiently eliminate tumors at a physiological tolerable temperature (Figure 4b). 76 The authors prepared a vortex-domain iron oxide nanoring and graphene oxide (FVIOs-GO) hybrid nanoparticle. Such nanoplatform has high thermal conversion efficiency and significantly amplified ROS level under an alternating magnetic field (AMF). The amplified ROS generation acted as the dominant factor in provoking a strong immune response below 40 °C in a hypoxic tumor microenvironment. This nanoplatform also leads to the exposure of CRT on the 4T1breast cancer cell surface, direct promotion of macrophage polarization to pro-inflammatory M1 phenotypes, and further elevation of tumor-infiltrating T lymphocytes. As therapeutic targeting is complicated by multiple facets of the tumor microenvironment, multiple mechanisms are needed to kill the tumor cells. 81,82 Different therapeutic modalities combined together could provide opportunities to exploit the advantages and offset the disadvantages of each therapeutic modality, leading to additive or even synergistic therapeutic effects. For example, the combination potentially increases the antitumor efficacy at lower doses of drugs/agents and lower-power light irradiation, enhances permeability in tumor sites and improves the local immune suppressive state. 27,81,83 Thus combining different ICD modalities together could minimize potential toxicity to non-malignant tissues and enhance immune responses.

Dual-modal ICDs for inducing tumor vaccine

The details are shown as follows.

The combination of chemotherapy and PDT (chemo-PDT) could induce synergistic therapeutic effects. Chemotherapy could address the limitation of light penetration and might also enhance the sensitivity of cancer cells to PDT. PDT with the ability of accelerating chemo-drug release from the endo/lysosomes by light irradiation could help to overcome chemo-resistance. 81 The chemo-PDT might also enhance treatment efficacy owing to inhibition of drug-efflux P-glycoprotein pumps in multidrug resistance cells resulting from ROS generation by the photosensitizer. 27,83,84 Recently, chemo-PDT has been introduced into ICD based immune therapy. For example, Hu et al. reported the use of chemo-PDT with ROS-sensitive lipid-polymer hybrid nanoparticles TK HNP-C/D to potentiate the antitumor efficacy of αPD-L1 (Figure 5a). 46 TKHNP-C/D not only induced PDT under 660nm irradiation but also rapidly degraded the hydrophobic TK-PPE core to boost intracellular DOX release, thus promoting an efficient cascade of chemo-PDT to inhibit tumor growth. More importantly, the cascade chemo-PDT could evoke anticancer immune responses and efficiently synergize with αPD-L1 to generate an abscopal effect, which could simultaneously inhibit primary and distant tumor growth.

The combination of PDT and PTT (PDT-PTT) has potential synergistic effects. The heating effect of PTT can enhance the intracellular delivery of photosensitizers as well as improve local blood flow and increase the oxygen concentration in tumor tissues, thus resulting in a higher PDT efficacy.

Additionally, ROS generated during PDT can disrupt heat-shock proteins, thereby negating their protective effects in tumor cells during PTT. 27 Recently, PDT-PTT has been introduced into immune therapy and shown enhanced anti-tumor efficacy. For example, Li et al. reported a type of nanosystem consists of ER-targeting pardaxin (FAL) peptides modified-, indocyanine green (ICG) conjugated-hollow gold nanospheres (FAL-ICGHAuNS), together with an oxygen-delivering hemoglobin (Hb) liposome (FAL-Hb lipo),designed to reverse hypoxia (Figure 5b). [START_REF] Li | [END_REF] Compared with non-targeting nanosystems, the ER-targeting system induces robust ER stress and calreticulin (CRT) exposure on the cell surface under NIR light irradiation. CRT, a marker for ICD, acts as an 'eat me' signal to stimulate the antigen presenting function of dendritic cells. As a result, a series of immunological responses are activated, including CD8 + T cell proliferation and cytotoxic cytokine secretion. In conclusion, ER-targeting PDT-PTT promoted ICD-associated immunotherapy through direct ROS-based ER stress and exhibited enhanced anti-tumor efficacy The combination of PTT and chemotherapy (Chemo-PTT) produces synergistic therapeutic effects. Chemotherapeutics could address the limitation of light penetration in PTT and might also enhance the sensitivity of tumor cells to hyperthermia. The heating effect of PTT can enhance local blood flow, delivery of the chemo-drugs and oxygen concentration in tumor tissues. 27,85 Recently, chemo-PTT has been introduced into ICD based immune therapy. For example, Wen et al. reported a new therapeutic system (Pd-Dox@TGMs NPs) made from Dox and a photothermal reagent palladium nanoparticles(Pd NPs) into amphiphilic triglycerol monostearates (TGMs) (Figure 5c). 86 It was proved that co-delivery of Dox and Pd NPs not only effectively killed CT26 cells through chemotherapy and photothermal therapy but also promoted the release of dangerous signaling molecules, such as HMGB-1, CRT, and ATP, improving the immunogenicity of dead tumor cells.

The effective ICD induction mediated by Pd-Dox@TGMs NPs boosted the PD-L1checkpoint blockade effect, which efficiently improved the infiltration of toxic T lymphocytes at the tumor site and showed excellent tumor treatment effects to both primary and abscopal tumors.

Preparation of tumor antigens ex vivo

Looking for effective tumor antigens has been pursued and studied for over a hundred years. As every tumor has its own unique composition of mutations with only a small fraction shared between patients, 1 tumor antigens have been designed from multiple tumor associated antigens to tumor specific antigens for a single patient. Several strategies have shown the advantage of personalization, including tumor lysate based vaccine, [START_REF] Shi | [END_REF]7 tumor cell membrane based vaccine 8,9 and neoantigen 87,88 .

Tumor lysate and tumor cell membrane could be obtained from human-derived cells/tissues. Using ex vivo tumor cells/tissues maintains biological property and molecular heterogeneity of the original tumor in the patient. 89 On the other hand, neoantigens are identified through ex vivo detection of patient's normal cells and tumor cells with genomic sequencing technology. All these three strategies need ex vivo technologies to manipulate tumor cells/tissues. With the progress of nanotechnology, nano-delivery systems have shown very good prospects in delivering tumor antigens. These nanovaccines can be designed with diverse features, such as co-delivery with adjuvants, targeting to lymph nodes and APCs, reliable protection and efficient delivery for antigens, tunable antigen release and effective cross-presentation, etc.

Protein/peptide

Tumor-specific antigen (also called neoantigens), as antigen resulting from somatic mutations present in individual cancers, becomes reality due to next-generation sequencing technologies and computational analysis. Neoantigens, the protein sequences not present in normal tissues, have potential advantages including decreased central immune tolerance, and improved safety profile. 90 Neoantigens typically have a high predicted binding affinity to MHC molecules and the ability to induce both CD8 + and CD4 + . 91 Despite promising, neoantigen-based cancer vaccines suffer from insufficient activation of the DCs, which limited their therapeutic performance in clinic. The nanodelivery systems have attracted increasing attention for their roles as antigen protectors and carriers.

With further functionalization, these particles could facilitate the access of antigens to APCs, alter intercellular trafficking and enhance accumulation at the lymph nodes.

There is a general need for antigen delivery vehicles that induce a more potent, antigen-specific CD8 + cytotoxic T cell (CTL) response. Induction of such a response requires antigen presentation via MHC-I. Exogenous antigens are endocytosed by APCs and degraded into peptides within compartments of the endo/lysosomal processing pathway. Peptides generated in these compartments are predominantly presented on the cell surface via MHC-II complexes, giving rise to CD4 + T cell responses. 92 Elaborately designed carriers have been demonstrated to evade lysosome degradation and stimulate cross-presentation. It has been reported that nanoparticles bearing positively charged polymers/peptides can facilitate antigen escape from the lysosome, reflecting a "proton sponge" effect, and upregulate MHC I complex expression. 93,94 Although these positive results are encouraging, harsh preparation conditions, complicated modification processes, and the biosafety concerns of the added materials have slowed their progress. To solve the aforementioned problems, Wang et al. fabricated hierarchical ovalbumin@CaCO3 nanoparticles. 95 This type of nanoparticles can efficiently ferry cargo antigen to dendritic cells, blast lysosomes for antigen escape to the cytoplasm and induce autophagy through the LC3/Beclin 1 pathways. These outcomes cooperatively promote antigen cross-presentation, elicit CD8 + T cell proliferation, ignite a potent and specific CTL response, and finally achieve prominent tumor therapy effects.

DCs are the key coordinators in tumor immunotherapy and the pivotal cell subsets to connect innate and adaptive immunity for antigen uptake and presentation, and eventually cross-priming the naive T-cells for activating the tumor-specific CTLs. Besides antigen degradation by lysosome of APCs, limited accumulation at the lymph nodes and cellular uptake by DCs also seriously slowed the progress of neoantigens. Zhou et al. reported a type of nanovaccines constructed from an acidactivatable micellar nanoparticle, neoantigen, and a stimulator of interferon genes (STING) agonist, 5,6-dimethylxanthenone-4-acetic acid (DMXAA) (Figure 6a). 14 Functionalization with mannose (Man) enhanced cellular uptake by macrophages and B cells in the lymph nodes due to the APCtargeting ability of the mannose receptor, while the acid-responsiveness facilitated cytosol release of the neoantigens. Meanwhile, the STING agonist activated the STING pathway in the DCs to elicit interferon β secretion and to boost T cell priming with the neoantigen. The nanovaccine dramatically inhibited tumor growth and occurrence of B16-OVA melanoma and 4T1 breast tumors in immune-competent mouse models. Combination immunotherapy with the nanovaccines and anti-PD-L1 antibody demonstrated further improved antitumor efficacy in 4T1 breast tumor model.

Cell lysate

Tumor cells have been shown to express antigens that can be recognized by immune cells and induce immune responses. Whole-cell tumor vaccines have been studied for several decades as they present many advantages compared to single-target vaccines. 96 First, whole tumor cells provide multiple characterized and uncharacterized tumor antigens that can be targeted by both the innate and adaptive immune systems. Second, whole-cell vaccination does not need the laborious experiences for antigen identification. Third, whole-cell vaccination may greatly decrease the probability of tumor escape. Furthermore, processing whole tumor derived repertories of tumor antigens and presenting them through both MHC class I and class II pathways in the presence of costimulatory molecules lead to a stronger overall anti-tumor response and long-term CD8 + T cell memory via CD4 + T cells. [96][97][98] However, soluble tumor lysates containing antigens and cytokines are inherently unstable and tend to result in poor DC uptake, inefficient antigen cross-presentation, and limited induction of immune response. [START_REF] Shi | [END_REF]7,99,100 Encapsulating tumor cell lysate into biomaterial-based nanoparticles has been proposed as a promising strategy to enhance immune responses. Biomaterial encapsulation not only could protect the antigens degradation during in vivo administration, but also enhance antigen delivery and subsequent induction of T cell mediated immune responses. [START_REF] Shi | [END_REF]99 Surface of biomaterials could be modified with ligands or antibodies that are specifically recognized by DCs and used for DC targeting. For example, Shi et al. reported whole tumor cell lysates combining mannose-chitosan nanoparticles as nanovaccine for tumor immune-therapy. [START_REF] Shi | [END_REF] The result demonstrates the possibility of using mannose as effective DC targeting ligand by conjugation of mannose with biomaterials to facilitate DC maturation, antigen uptake and presentation. Furthermore, by encapsulating tumor cell lysates generated from B16 melanoma cells, mannose-chitosan-tumor cell lysates nanoparticles could effectively stimulate cellular and humoral antitumor immunities.

Tumor lysate is usually used in tumor vaccine based on ex vivo modifying DCs. Promising experimental data have indicated that such DC-based vaccines can sufficiently generate primed DCs.

However, challenges still remained with these primed DCs, including the poor migration efficiency of primed DCs to lymph node, the labor intensive productive process, and the burdensome medical expenditure. Nanotechnology presents good potential in fulfilling these requirements through enhancing antigen delivery and dealing with immune tolerance accompanied with tumor development. For example, Hu et al. reported a type of lipid zinc phosphate hybrid nanoparticles (LZnP NPs) loaded with MPLA and B16F10 melanoma cell-derived tumor lysate for vaccination (Figure 6b). 97 LZnP nanovaccine can efficiently prime DCs and induce cytotoxic T lymphocytes response. To regulate immune tolerance, the PD-L1 antagonist, d-peptide antagonist ( D PPA-1), is involved in treatment. Tumor lysate-loaded LZnP nanovaccine with D PPA-1exhibits the anticipated tumor inhibition on therapeutic and prophylactic melanoma models with extended survival time.

Cell membrane

There are many antigenic motifs on the cell surface, and cytotoxic T lymphocytes (CTLs) usually recognize tumor cells via the tumor cell membrane. Isolation of individual membrane factors enabled coating of nanoparticles with cell membranes. To date, the tumor cell membrane based nanovaccines have exhibited great potential in cancer immunotherapy. Combing both synthetic components and natural cell membrane yields a unique class of biomimetic materials, which could prolong circulation time and enhance selective targeting ability, ultimately leading to significant therapeutic potential. 21 More importantly, biomimetic nanoparticles are able to inherit the homologous property from cancer cells, and are considered as an effective strategy for personalized cancer treatment. 89,102 The preparation and performance evaluation of these nanoparticles were mostly based on cell lines and cell-line-based xenograft mouse models. However, there are significant differences between cell lines and human-derived cells. Rao et al. reported gelatin nanoparticles (GNPs) coated with head and neck squamous cell carcinoma (HNSCC) patientderived tumor cell (PDTC) membranes. 89 The resulting PDTC@GNPs efficiently targeted homotypic tumor cells and tissues in patient derived xenograft models, indicating that tumor cell membrane based nanoparticles could be an effective strategy for personalized cancer treatment.

Cancer immunotherapy mainly focuses on manipulating patient's own immune system to recognize and destroy cancer cells. Vaccine formulations based on nanotechnology have been developed to deliver antigens to APCs and to improve antigenicity by combining with adjuvants.

For example, Jin et al. reported biomimetic PLGA NPs coated with human cancer cell membrane fractions (CCMFs). 103 CCMFs and CCMF-PLGA NPs were capable of inhibiting cancer cell migration toward human mammary fibroblasts. Intravenous injection of CCMF-PLGA NPs significantly reduced experimental metastasis in vivo. A higher percentage of CD8 + and CD4 + cytotoxic T-lymphocyte populations was observed in spleens and lymph nodes. Splenocytes isolated from CCMF-PLGA NP-immunized mice had the highest number of interferon gamma-producing T-cells. These data show that CCMF-PLGA NPs could be promising for disrupting cancer cell-stromal cell interactions and for priming the immune system in cancer immunotherapy. Noh et al. reported multifaceted immune-modulatory nanoliposomes (denoted as "tumosomes") that use tumor cell membrane proteins as tumor-associated antigens for reshaping the immune response in the lymph node and enhanced antitumor immunity (Figure 6c). 101 Two lipid-based adjuvants, monophosphoryl lipid A and dimethyldioctadecylammonium are used as danger signal and cellinvasion moiety, respectively. Tumosomes are able to provide tumor antigens and molecular adjuvants for the priming of a long-term adaptive immune response in tumor draining lymph nodes and in the spleen.

Immuno-modulatory molecules

Immuno-modulatory molecules are essential components in vaccine formulations to induce robust immunity against tumor antigens. By combination of immuno-modulatory molecules with nanoparticle mediated therapeutic vaccines, it is possible to achieve complete eradication of tumors and induce long-term anti-cancer immunity. In nanoparticle-mediated tumor vaccines, several immuno-modulatory molecules have been extensively investigated, including immune checkpoint molecules, nucleic acids, imidazoquinoline derivatives, polysaccharides and cytokines (Table 1). 1). These combinations allowed to significantly potentiate checkpoint, and to generate long-term anti-tumor immunity, thus showing much promise in treating "cold" tumors. 51,52,65,74 Antagonists of CTLA-4 (ipilimumab 105,108 and tremelimumab 109 ), PD-1 (pembrolizumab 114 and nivolumab 105 ), PD-L1 (durvalumab 109 and D PPA-1 97 ) have been used for generating tumor vaccines. Agonists of CD137 and OX40 also have been applied in tumor vaccines. 111,116 Nucleic acids, which are derived from DNA or RNA of microbial pathogens, are the main agonists of toll-like receptors (TLRs). TLRs are single, membrane-spanning, non-catalytic receptors usually expressed in sentinel cells such as macrophages and dendritic cells. They play an important role in the activation of the innate immune system and in shaping the adaptive immune system. TLRs could recognize highly conserved structural motifs known as pathogen-associated microbial patterns which are exclusively expressed by microbial pathogens. However, these DNA/RNA adjuvants alone suffer from insufficient immunogenicity and -in the case of RNA -low stability. 135 In order to enhance immune responses, these adjuvants have been encapsulated in nanoparticles and combined with other therapeutic strategies (Table 1). In DNA adjuvants, immune-stimulatory Imiquimod (R837) and resiquimod (R848) are imidazoquinoline derivatives which are one of the most widely investigated groups of TLR agonists. R-837 occurs particularly via the TLR-7 and stimulates the innate immune response through induction, synthesis, and release of cytokines, including interferon-a (IFN-a), interleukin (IL)-6, and tumour necrosis factor (TNF)-a. 137 R-848 is a TLR7 and TLR8 agonist that induces the upregulation of cytokines such as TNF-α, IL-6 and IFNα. [138][139][140] Polysaccharides belong to a class of natural polymers consisting of glycosidically linked carbohydrate monomers. As vaccine adjuvants, polysaccharides can not only promote antigenspecific immune system, but also enhance the body's natural immune functions. [143][144][145] Polysaccharide adjuvants mainly include lipopolysaccharide, glucan, mannan, inulin, chitosan and its derivatives. Some of them have been used as adjuvants in combination with tumor vaccines (Table 1). For example antigen are usually less toxic, for the tumor components and delivery systems present good biocompatibility. ⑥Both strategies have been reported for the treatment of "cold" immune tumors which usually have a low level of mutations, express few neoantigens, lack of tumor-infiltration lymphocytes (TILs) and cytotoxic T cells(CTLs). 74,146 These tumors do not respond to immunecheckpoint therapy. It has been demonstrated that ICD would be a hopeful way for enhancing CTLs infiltration and converting a "cold" tumor to a "hot" one. [146][147][148][149] Moreover, studies also have shown that neoantigens are potent T-cell activators, and are thus promising strategies for turning a "cold" to a "hot" tumor immune microenvironment. Applicable for "cold" tumors ICD could increase CTLs infiltration and turn "cold" tumors to hot ones.

Comparison of in vivo and ex vivo strategies to prepare tumor antigens

Neoantigens are potent T-cell activators, and turn "cold" tumors to "hot" ones.

Conclusion and perspectives

Tumor antigens could be induced in vivo or prepared ex vivo. Both strategies allow to realize personalized therapy to patients, turning a "cold" into a "hot" immunogenic tumor microenvironment and inducing long term immunological memory response. There are also advantages and disadvantages when they are compared to each other. Inducing tumor antigen in vivo has the advantage of generating DAMPs, however, chemo-drugs or PDT/PTT/MTT agents may be toxic or non-biodegradable. Preparing tumor antigen ex vivo usually has good biocompatibility, but this strategy could not generate DAMPs. Combining immune therapy with nanotechnology could further enhance immunotherapy effect owning to unique advantages of smart nanosystems, such as increasing immune response at lower doses of drugs/agents and lower-power light irradiation, further encapsulating immuno-modulatory molecules or combining with other therapy treatments. ROS/heat generating nanoparticles have been evaluated for inducing tumor antigen release in vivo, while antigen delivery nano-systems have been synthesized for processing tumor antigen ex vivo.

Various nanoparticles prepared from inorganic compounds and polymers have been evaluated for improving the outcomes while limiting the systemic toxicity. A large number of strategies (e.g.

different ICD inducers and tumor antigen delivery systems), nano-formulations and adjuvants, have been reported. However, few comparative data are available on these different approaches, particularly in humans. In addition, translational potential of nanomaterials remains low owing to poor stability, insufficient tumor accumulation, toxicity, and difficulty to scale up. Therefore, fundamental issues need to be addressed, including the most effective type of nanoparticle platforms, adjuvant, dose, administration route and schedule. Last but not least, nanoparticles should be safe, stable, preferably with a single dose and a maximum of two doses, and have the ability to induce long-lived memory B and T cell responses so as to achieve efficient tumor vaccine for personalized therapy.

Figure 1 .

 1 Figure 1. Preparation of tumor antigens through in vivo or ex vivo strategies and their immune responses

Figure 3 .

 3 Figure 3. ROS-generating nanoparticles to induce tumor vaccines (a) Ce 6 encapsulated C@HPOC nanoparticles

Figure 4 .

 4 Figure 4. Heat-generating nanoparticles to induce tumor vaccines. (a) Thermal responsive lipid gel loaded with

Figure 5 .

 5 Figure 5. Two ICD inducers combined together for inducing tumor vaccines (a) ROS-sensitive hybrid TK HNP-C/D

Figure 6 .

 6 Figure 6. Nanoparticle-based vaccine delivery systems:(a) Combination immunotherapy with neoantigen-based

  sequences (CpG motifs) present in DNA of bacterial origin are used. Synthetic oligodeoxynucleotides containing CpG motifs (CpG-ODNs) could activate TLR9 on variety of APCs to produce various inflammatory cytokines including IL-1, IL-6, IL-8, IL-12, TNF-α, and IFN-γ. 136 Polyinosinic:polycytidylic acid (poly(I:C)) is a synthetic analog of double-stranded RNA, and acts as agonist of TLR 3 and retinoic acid inducible gene I (RIG-I)-like receptors (RIG-I and MDA5). 141, 142

  , 3-O-desacyl-4'-monophosphoryl lipid A (MPLA), a nontoxic derivative of the lipopolysaccharide of Salmonella minnesota R595, could act as TLR4 agonist and induce the production of IFN-γ and IL-12.145 Chitin, a linear β-1-4-linked polymer of D-glucosamine and Nacetyl-D-glucosamine extracted from shrimp, and chitosan, which is obtained by partial deacetylation of chitin, exhibit a range of immunological effects, including macrophage activation and production of inflammatory cytokines including IL-12, IL-18, TNF-α and IFN-γ and enhanced antibody production when co-administered with antigens.129, 130 Cytokines, a group of regulatory peptides or glycoproteins with molar masses below 30 kDa, have been widely recognized as crucial factors in tumor development and treatment. They are secreted by various cells of the immune system (innate as well as adaptive) that help to regulate and boost immunity. At the top of the inflammatory cytokine cascade are granulocyte-macrophage colony-stimulating factor (GM-CSF) and some interleukins. A number of cytokines have been used in combination with tumor vaccines. For example, GM-CSF can promote antigen presentation, IL-2 production, antibody secreting, and enhance the function of CD4 + and CD8 + T cells. IL-2 is required for the development and secondary expansion of memory T cells, and it also supports the growth and expansion of NK cells as well as other immune cells such as B cells at various stages of development or activation. IL-12 induces the production of IFN-γ and stimulates TH1 and NK cell growth, while inhibiting TH2 cell responses.

Table 1 .

 1 Immuno-modulatory molecules used in tumor vaccines

	Classification	Molecule	Mechanism	Usage in tumor vaccine
	Immune	Anti-CTLA-4 antibody	CTLA-4 antagonist	Combined with PDT 104 , chemotherapy 105 ,
				radiotherapy 106-109 , PTT 110
	checkpoint
		Anti-PD-1 antibody	PD-1 antagonist	Combined with PDT 111 , chemotherapy 105, 112,
	molecule
				radiotherapy 113, 114 , PTT 115, OVA 116
		Anti-PD-L1 antibody,	PD-L1 antagonist	Combined with PDT 45 , radiotherapy 109, 117 , PTT 74 ,
				OVA 14 , chemo-PPT 86 Combined with tumor
		PD-L1-blockade siRNA,
				lysate 97
		Peptide
		Anti-CD137 antibody	CD137 agonist	Combined with OVA 116
		Anti-OX40 antibody	OX40 agonist	Combined with PDT 111
	Nucleic acid	CpG ODNs	TLR9 agonist	Combined with PDT 49 , chemotherapy 118 , PTT 119 ,
				tumor cell lysate 120 , tumor antigen OVA 121
		Poly (I:C)	TLR3, RIG-I/MDA5 agonist	Combined with chemotherapy 19 , OVA 123
	Imidazoquinoline	Imiquimod (R-837)	TLR7 agonist	Combined with PDT 122 , PTT 70, 73 , cell membrane
	derivatives			based vaccine 8 , OVA 123 , chemo-PTT 124 , PDT-
				PTT 125
		Resiquimod (R-848)	TLR7, TLR8 agonist	Combined with chemotherapy 126 , PTT 75 , OVA 127
	Polysaccharide	MPL A	TLR4 agonist, induce IFN-γ	Combined with tumor cell membrane 101 , OVA 128
			and IL-12
		Chitosan and its	macrophage activation, induce	Combined with radiotherapy 129 , OVA 130
		derivates	IL-12, IL-18, TNF-α and IFN-γ
	Cytokine	GM-CSF	enhance antigen presentation,	Combined with MTT 131 , OVA 132
			induce IL-2

  Tumor antigens could be induced in vivo or prepared ex vivo. There are similarities and differences between two strategies as shown in table 2, and the details are as follows. ①Strategies for inducing tumor antigen release in vivo usually include chemotherapy, radiotherapy, PDT, PTT or MTT. The ROS/heat generating from focused effect or collateral effect could induce ICD and antigen release through ER stress. Strategies for preparing tumor antigens ex vivo aim at revealing efficient tumor antigens, mainly neoantigen which could induce stronger immune response and realize personalized therapy. ②ROS/heat generating nanoparticles are designed to induce tumor antigen release in vivo. Nanotechnology also has been used to prepare tumor antigens ex vivo via antigen delivery nano-systems which allows enhance the delivery of tumor antigens to APCs. ③ Inducing tumor antigens in vivo is accompanied by generating DAMPs that recruit APCs and stimulate optimal antigen presentation to T cells, while the ex vivo strategies could not. ④Both two strategies could induce CD8 + (cytotoxic) and CD4 + (helper) T cells. ⑤Inducing tumor antigen in vivo usually has side effects which are induced by chemotherapeutic drugs, photosensitizers or hyperthermia agents. Fortunately, nanotechnology could reduce related side effects through controlling drug release, and enhancing the targeting, etc. Ex vivo strategies for preparing tumor

Table 2 .

 2 150, 151 Comparison of in vivo and ex vivo strategies to prepare tumor antigens

	Property	In vivo strategy	Ex vivo strategy
	Mechanism	Chemotherapy, radiotherapy, PDT, PTT, MTT	Looking for efficient tumor antigens
	Role of nanoparticles	Enhance ROS/heat generation in tumor sites	Protect and deliver tumor antigens to APCs
	Generation of DAMPs	Generate DAMPs	Cannot generate DAMPs
	Induction of T cells	Induce both CD8 + and CD4 + T cells	Induce both CD8 + and CD4 + T cells
	Related side effect	Chemo-drugs, PDT/PTT/MTT agents may be	Antigen delivery systems have good biocompatibility.
		toxic or non-biodegradable

Acknowledgements

This work was supported by the science and technology innovation commission of Shenzhen (JCYJ20170817094609727) and Shandong provincial natural science foundation of China (ZR2020MH324, ZR2020QH271).

Conflicts of interest

The authors declare no competing financial interest.


domain: sdu sde

text:
Úna C Farrell

Rifaat Samawi

Anjanappa Savitha

Roman Aionis

Aionis Klykov

O Oyeleye

Adeboye Boone

Heda Agic

Anne-Sofie C Ahm

Thomas H Boag

Jochen J Brocks

Tessa N Brunoir

Donald E Canfield

Xiaoyan Chen

Meng Cheng

Matthew O Clarkson

David R Cordie

Peter W Crockford

Huan Cui

Tais W Dahl

Lucas D Mouro

Stephen Q Dornbos

Julie A Dumoulin

Joseph F Emmings

Cecilia R Endriga

Tiffani A Fraser

Robert R Gaines

Richard M Gaschnig

Timothy M Gibson

Benjamin C Gill

Karin Goldberg

Romain Guilbaud

Galen P Halverson

Kalev G Hantsoo

A Henderson

S W Hodgskiss

Tristan J Horner

Jon M Husson

Benjamin Johnson

C Brenhin Keller

Michael A Kipp

Andrew H Knoll

Marcus Kunzmann

Florian Kurzweil

Matthew A Leroy

Alex G Lipp

David K Loydell

A Macdonald

Joseph M Magnall

Kaarel Mänd

Michael J Melchin

J Miller

Dr M Och

A G Von Moos

Frantz Ossa Ossa

Camille A Partin

Shanan E Peters

Peter Petrov

L Playter

Stephanie Plaza-Torres

Susannah M Porter

Simon W Poulton

Sara B Pruss

Sylvain Richoz

Samantha R Ritzer

Alan D Rooney

Swapan K Sahoo Equinor

Shane D Schoepfer

Judith A Sclafani

Oliver Shorttle

Sarah P Slotznick

Emily F Smith

Sam Spinks

Richard G Stockey

Justin V Strauss

Sabrina Tecklenburg

Nicholas J Tosca

Gabriel J Uhlein

Huajian Wang

Philip R Wilby

Christina R Woltz

Rachel A Wood

Inessa A Yurchenko

Tianran Zhang

Noah J Planavsky

Kimberly V Lau

David T Johnston

Dr Erik A Sperling

The Sedimentary Geochemistry and Paleoenvironments Project

Introduction

Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics.

Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated towards larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses.

In this paper we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal is to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared to fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal is to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history.

With respect to the data product, SGP is focused on assembling a well-vetted and comprehensive dataset that is tractable to multivariate statistical analyses accounting for multiple geological and methodological biases. Phase 1 of the project, which focuses on the Neoproterozoic and Paleozoic, has been completed. Future phases will capture a broader range of geologic time, data types, and geography. The database contains tens of thousands of unpublished data points provided by consortium members, as well as detailed metadata that go beyond what is contained in papers. In many cases, these represent measurements that are tangential to a given published study but still of high utility to database studies; these allow the community to address questions that would be impossible to answer solely with the published data. For instance, in order to use a proxy such as Mo/TOC (total organic carbon) ratios in mudrocks deposited under a euxinic water column, the full suite of trace metal, iron speciation, and total organic carbon data is needed. Likewise, geospatial information is required to account for sampling biases, and many statistical learning approaches cannot accept, or have difficulty with, incomplete geological predictor variables.

Ultimately, it is this complete data matrix that will allow for SGP's most insightful analyses. This paper serves as an introduction to SGP, the process by which our data products are created, a description of the Phase 1 data product and a citable reference for that product, a description of the SGP website and API (Application Programming Interface) for open access, and a statement of our future goals.

Why SGP?

In recent years there has been a welcome trend in the broader geochemical community towards increased data accessibility, documentation of sample context, and sample curation, albeit with challenges still ahead [START_REF] Brantley | A Vision for the Future Low-Temperature Geochemical Data-scape[END_REF][START_REF] Cutcher-Gershenfeld | Build It, But Will They Come? A Geoscience Cyberinfrastructure Baseline Analysis[END_REF][START_REF] Planavsky | Store and share ancient rocks[END_REF]. First, progress has been made through journals and organizations adopting stringent data archiving rules and promoting adherence to FAIR principlesfindability, accessibility, interoperability, and reusability ("FAIR Play in Geoscience Data," 2019; [START_REF] Wilkinson | The FAIR Guiding Principles for scientific data management and stewardship[END_REF].

Second, several databases now house geochemical data at different scales and with different focuses (e.g., [START_REF] Brantley | A Vision for the Future Low-Temperature Geochemical Data-scape[END_REF][START_REF] Gard | Global whole-rock geochemical database compilation[END_REF][START_REF] He | A review of geoanalytical databases[END_REF][START_REF] Lehnert | A global geochemical database structure for rocks: geochemical database structure[END_REF]. Among the largest and most active are projects such as EarthChem (earthchem.org), the Geobiodiversity Database (geobiodiversity.com), Pangaea (https://www.pangaea.de), and the StabisoDB (https://cnidaria.nat.uni-erlangen.de/stabisodb/). The SGP database was built with the data structures and standards of these other projects in mind, in keeping with FAIR principles and with the hope that data can be easily shared in the future. Consistent with the stance taken by other organizations in the community (e.g., [START_REF] Hanson | AGU Opens Its Journals to Author Identifiers[END_REF], we also strongly encourage all members to register their samples for an International Geo Sample Number (IGSN; i.e., globally unique alphanumeric sample identifiers), which can be obtained from the System for Earth Sample Registration (www.geosamples.org). However, SGP is a domain-specific project that differs from other databases in the way the data are collected, the nature of the data collected, and the tailored way in which they are presented to our research community. Specifically, SGP is focused on addressing how geochemical proxy records change through deep time. Central to these goals are the following:

1) Compilation of a large quantity (i.e., millions of records) of sedimentary geochemical data spanning deep time.

2) Appropriate age models (with uncertainty), especially for Proterozoic/Archean samples.

3) Information on interpreted depositional environment and specific rock type. 4) Information necessary to gauge if samples are likely to preserve primary, environmental geochemical signals.

5) Detailed methodological information on how the data were generated.

6) An ability to download the data of interest flexibly and easily.

Although some other databases contain sedimentary geochemical data, the vast majority of deep time data is not available from any single source, and samples are not readily associated with critical contextual data-such as age constraints and environmental data-necessary for the types of proxy-through-time and/or environmental studies typically conducted in historical geobiology.

When the SGP was founded in 2015, we believed that a 'team science' philosophy would be the most effective way to move beyond spreadsheets to the type and abundance of data required. The research consortium framework we have implemented is modeled after mature consortia in human statistical genetics, such as the Psychiatric Genomics Consortium (PGC). In the PGC, researchers have aggregated data to make statistically robust observations and landmark findings not possible with the data generated by any single research group alone (Duncan et al., 2017;Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014; Wray et al., 2018). Similar to biomedical research consortia, we hope that the intellectual and collaborative environment fostered by SGP will ultimately be as important as our data products or specific insights in research papers.

The first priority for Phase 1 of SGP was to assemble or generate multi-proxy sedimentary geochemical data (carbon and sulfur abundances and isotopes, iron speciation, major and trace metal abundances, and trace metal isotopes, primarily from fine-grained siliciclastic rocks) from multiple regions worldwide for every Paleozoic Epoch and equivalent ~25 Myr Neoproterozoic time slices. In addition to data compilation, this has involved an effort by SGP members to generate new geochemical data from 'background' intervals in the Paleozoic (i.e., not associated with events such as mass extinctions or significant climatic shifts). The first phase of data collection came to an end in 2019. At that point a copy of the database was vetted by SGP team members and then archived-the first data 'freeze' (following the best-practices approach used in medical consortia).

Working Groups were formed (with working group leadership established through an open call to SGP team members), and data were made available to Working Group analysts via the website and through tailored queries. The first Working Group papers have recently been published [START_REF] Leroy | Variable redox conditions as an evolutionary driver? A multi-basin comparison of redox in the middle and later Cambrian oceans (Drumian-Paibian)[END_REF][START_REF] Lipp | The composition and weathering of the continents over geologic time[END_REF][START_REF] Mehra | Curation and Analysis of Global Sedimentary Geochemical Data to Inform Earth History[END_REF], and more are in progress. Meanwhile, data collection continues, and the Phase 2 goal is to include more Mesozoic-Cenozoic and pre-Neoproterozoic time intervals and to expand the geochemical record to more diverse lithologies and grain-specific phases. The Phase 2 data freeze is currently anticipated for 2023, followed by data vetting and analyses towards group papers.

Database

SGP utilizes a relational database implemented with the PostgreSQL database management system.

A full database diagram and documentation are available at https://github.com/ufarrell/sgp_phase1 and a simplified diagram is shown in Fig. 2. The design was inspired by several existing data models in the geological and natural history museum communities. Tables for analytical geochemistry are from the British Geological Survey (BGS) geochemistry data model [START_REF] Watson | Open Geoscience Data Models: End of project report[END_REF], with minor modifications. Tables for geological, geographical and sample details are based on established museum collection management databases (Specify 6 https://www.specifysoftware.org/ and Arctos https://arctosdb.org/) in addition to the Observations Data Model 2 (ODM2, [START_REF] Horsburgh | Observations Data Model 2: A community information model for spatially discrete Earth observations[END_REF][START_REF] Hsu | Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2)[END_REF], an information model for Earth observations.

The SGP database is centered on the sample table (Fig. 2). Samples are generally characterized by an individual rock sample and all resulting analyzed powders. The three key sections of the database linked to samples are (1) analytical results and associated methods, (2) geographical context, and (3) geological context. Dictionary tables (standardized lists of terms, also known as 'controlled vocabularies') are based on existing community vocabularies where possible (e.g., from EarthChem, ODM2, Macrostrat, U.S. Geological Survey (USGS), and BGS). However, in many cases these vocabularies required additions, such as the inclusion of specific sedimentary geochemical experimental methods (e.g., sequential iron extraction techniques [START_REF] Poulton | Development of a sequential extraction procedure for iron: Implications for iron partitioning in continentally derived particulates[END_REF]).

The BGS data model for analytical methods and geochemical results has been adopted almost without modification. We store analytical data in their submitted or published format, and do not standardize the results to any given unit. An analytical result may be empty (NULL) only if it is below or above detection limits, and those values are also stored if they are available. If the results are published, they are linked directly to a reference work on an individual basis so that a fine-level distinction can be made between published and related unpublished data from the same samples.

Any geostandards that are analyzed alongside samples in a study are also recorded.

In the SGP, we make every effort not to include the same result twice. However, replicates may legitimately be added if the same sample has undergone analysis for the same analyte more than once (this could include anything from true replicate analyses using the same methods in the same lab to analyses of the same sample by different research groups using different methods). We do not currently assign new sample identifiers to sub-samples. A parent-child relationship may be added in Phase 2 when the focus will expand to include carbonate data.

Data Collection

The SGP welcomes contributions from any interested researchers. Specifically, contributing data automatically makes a researcher part of the SGP Collaborative Team, rather than one needing to 'join' SGP to contribute data. In the first consortium-building stage, potential collaborators were targeted if their work was particularly relevant to the Phase 1 goals, and additional researchers were recruited via SGP representation at multiple conferences. SGP collaborators are involved in providing details about their samples and providing published data tables and unpublished data from their own archives. In addition, some data have been collected from relevant published studies where the authors are not directly involved. In such cases, contextual information was coded by SGP team members using information provided in the paper. SGP collaborators are asked to fill in a template with contextual information as completely as possible, but with an emphasis on key fields such as modern latitude and longitude, stratigraphic unit name, depositional environment, and lithology. A particularly important field is interpreted age, which is a numerical estimate for the age of each sample in millions of years (Ma). Whenever possible the original authors, who are most familiar with the samples and stratigraphic sections, are asked to provide the interpreted age. They can use whatever method with which they feel most comfortable; for example, ages may be estimated based on assumed sedimentation rates and/or linear interpolation, or groups of samples can be assigned one age based on proximity to any available time markers. A brief justification is required for each age provided, which may be used in the future to refine ages further. Maximum and minimum age estimates can also be stored, and indeed, are critical for the type of re-weighted bootstrap analyses employed by many SGP Working Groups [START_REF] Mehra | Curation and Analysis of Global Sedimentary Geochemical Data to Inform Earth History[END_REF].

A subset of samples from two USGS databases have been integrated into the SGP database. The first of the databases used is the National Geochemical Database: Rock (USGS NGDB, U.S.

Geological [START_REF] Survey | Geochemistry of rock samples from the National Geochemical Database[END_REF], comprising data from USGS projects from the 1960s-1990s, largely from North America. The second is the Global Geochemical Database for Critical Metals in Black Shales project (USGS CMIBS, [START_REF] Granitto | Global Geochemical Database for Critical Metals in Black Shales[END_REF], which includes predominantly Phanerozoic shale data from all continents. Data from both USGS databases lack much of the contextual information available for samples directly coded by the SGP team members (most specifically basin type, metamorphic grade, depositional environment, and detailed age justification) and there are a higher proportion of analytes with less detailed geochemical methodology. Nevertheless, they represent large numbers of samples (74% of samples in Phase 1 are from USGS sources) with age, lithology, and geographic information that can be utilized for many types of analysis.

In the case of USGS NGDB, only sedimentary samples were incorporated into SGP, and in the case of USGS CMIBS, we did not include samples with lithologies indicative of ore or studies where the authors were primarily concerned with mineral deposits or studying the effects of metamorphism on shales. An attempt was made to match USGS fields to SGP fields, with some data cleaning needed in order to extract important information such as up-to-date stratigraphic names. Samples can easily be traced back to the original USGS databases using their original identifiers.

The USGS NGDB data were enhanced by adding interpreted ages. Samples were matched, using a combination of stratigraphy and location, to the continuous time age model in Macrostrat [START_REF] Peters | Macrostrat: A Platform for Geological Data Integration and Deep-Time Earth Crust Research[END_REF]. Specifically, the minimum and maximum age estimates from the Macrostrat model were entered, and the interpreted age was entered as the average of these values. Only samples with matched interpreted ages were included from USGS NGDB. The USGS CMIBS samples were associated with Macrostrat continuous-time age models where possible and given age information by SGP team members where not. However, a proportion (36%) remain without ages, and filling those in is a key goal for Phase 2.

These three sources of data (direct entry by SGP team members (26% of samples), the CMIBS compilation (16% of samples), and the USGS NGDB (58% of samples)) provide a robust base platform for statistical analyses of aggregated sedimentary geochemical data through Earth history.

Moving forward, we will continue direct entry from the SGP team members, and work towards incorporating geochemical data compiled by additional geological surveys (for instance, incorporation of the OZCHEM whole rock database from Geoscience Australia is currently in progress).

Data Description Phase 1

Phase 1 of data collection ended in August 2019. A static version of the database was archived and made available to collaborators through the website (sgp-search.io) and via tailored queries. Time was allowed for vetting and any errors discovered were corrected before the final freeze in February 2020. The Phase 1 data freeze includes 82,578 samples, with 2,701,236 analytical results, and was made public through our search website in December 2020. This paper should be cited in the future use of Phase 1 data downloads. More complete information on the Phase 1 data product can be found on the SGP wiki (https://github.com/ufarrell/sgp_phase1/wiki), including summaries by age, lithology and geochemical methodology, as well as the specifics of how USGS databases were incorporated into the SGP structure.

SGP

The SGP-contributed dataset includes 20,811 samples with 518,291 results. Approximately two thirds of the data (64%) come from 160 published sources (https://github.com/ufarrell/sgp_phase1/wiki/SGP-data-references). The remaining 36% are from unpublished sources, including new and legacy data. The samples come from 942 individual sites from 46 countries (Fig. 3). Consistent with the Phase 1 goals, 84% of samples were from the Neoproterozoic-Paleozoic (Fig. 4). Sixty-four percent of samples are fine-grained siliciclastic rocks (shale, mudstone or siltstone), as are the majority of uncoded lithologies (Fig. 5).

USGS NGDB

The data from USGS NGDB that are incorporated into the SGP database include 48,234 samples with 1,769,696 results. Nearly all (99%) of the samples are from the United States. Nineteen percent are sandstone, 13% are shale, and 29% do not have a specific lithology (although lithological details may be available in verbatim fields; Fig. 5). Contextual details, including depositional environment and low-grade metamorphic bin, are mostly not available for these samples, and methodological information is sparse. In general, the USGS NGDB samples skew younger than the SGP samples: 39% are from the Paleozoic, 25% from the Mesozoic and 33% from the Cenozoic (~3% of samples are from the Proterozoic/Archean).

The USGS database provides excellent coverage of the United States, but given the remit of the organization, with strong focus on economic deposits (petroleum-producing units, phosphatic units, sedimentary mineral deposits), the sampling may not be representative of the entire country. This is distinct from the bias present in geochemical data produced by academic researchers, which are often focused on mass extinction intervals, Earth system perturbations, and other stratigraphic boundaries.

this is a small percentage now, we anticipate continued growth given the popularity and utility of handheld XRFs. A 'samples' search will list an individual sample on each row, with geological context information and geochemical analytes taking up the columns. Data are converted to one standard unit, oxides are converted to elements (e.g., Al2O3 to Al), and values are averaged if more than one analysis was made per sample. Note this search may average values produced using different analytical methods, although the number of samples in the database with multiple analytical values for a specific analyte is relatively small. Further, any analyses below or above detection limit are removed, as these cannot be averaged. This has implications for queries involving very low abundance elements (e.g., Ag in sedimentary rocks), as only results above detection limits, and thus higher values, will be included. We anticipate that this search will produce the optimal data output for most end-users interested in Earth history: a file with age, geological context and geochemical data for each sample.

If users are looking to delve deeper into the data and understand the analyses and procedures that were executed to obtain each sample's geochemical data, then the 'analyses' search is useful because it lists every analysis recorded in the database in a separate row. The 'analyses' search also allows users to show data relating to the lab where the sample was analyzed, the person who made the measurement, geochemical methodology, etc. At the current time, aside from the ability to exclude handheld XRF data, the 'samples' and 'nhhxrf' search types will not report information about, or have the ability to filter by, geochemical methodology. Users who are interested in methodological details or who would like to export a data file beyond the size limit (10 Mb) should contact the SGP Leadership Team regarding a custom SQL query.

Once the user has selected a search type, samples can be filtered based on both geological context and geochemical attributes. Note that for many samples some aspects of geological contextual information are incomplete. Thus, for example, a search filtering for samples deposited in a rift basin will only return samples positively described as such and not necessarily all samples in the database deposited in rift basins. Given that samples will have non-overlapping missing data, too many filters may result in a smaller-than-expected dataset.

Search results will appear in a 'preview' window that can be used to check the output. Each sample also has an information icon associated with it; clicking this icon will bring up a lightbox with detailed sample information. Finally, the user may request to show reference information for their search. For 'analyses' searches (where every analysis is shown as an individual row), this will return the specific literature citation for that analytic result. For other search types, this will return, for every sample, a concatenated list of all references whose geochemical data contributed to that specific search.

When the user is satisfied with their search, they can then download a .csv file of the data and export a map showing the location and age of samples in their search.

The SGP website uses an API to interact with the database, and users can make a copy of the API call using the API icon next to their search results. However, users can also bypass the user interface entirely and access data via a direct API call. This comprises three parts:

• type: Selects the search type (samples, analyses or nhhxrf)

• filters: Contains a list of search options that are logically ANDed in the results

• show: Contains search options that determine which columns will appear in the results

Thus, an example API call would be:

{"type":"samples","filters":{"country":["Argentina","Brazil","Chile","Bolivia","Colombia","Ven ezuela"],"toc":[2,100]},"show":["toc","fe","height_meters","section_name","country","interprete

d_age"]} This API call is making a 'samples' type search for samples that originate from Argentina, Brazil, Chile, Bolivia, Colombia, or Venezuela and have 2-100% total organic carbon (TOC) content. In other words, searching for organic-rich samples from South America. In addition, the API call is asking for a results output table with columns that show TOC (wt%), Fe (wt%), section or core name, collection height in meters, each sample's country, and the age in millions of years. Full documentation and a tutorial video are available on the website.

Future goals and directions

The overarching goal of SGP is to provide intellectual and geoinformatic resources for the Earth Science community to advance our understanding of environmental changes on Earth through time.

A better understanding of Earth's history requires sufficient data density, but equally importantly it means training a new generation of researchers with the data science and statistical skills to make meaningful conclusions from large sedimentary geochemical datasets. Much of the focus in SGP Phase 1 was in initiating the consortium and increasing the data product to the point where it was useful for analyses by the community. We aim now to increasingly move towards developing a community-initiated set of best practices for data management, a culture of publishing metadata, and a shared intellectual framework for analyzing such datasets. Over the course of Phase 2 we plan to continue holding annual meetings at Goldschmidt, while also beginning regular video calls to share progress and ideas for data analysis, as well as accessible geochemistry 'short courses' to help the geobiological community understand the strengths and weaknesses of different proxies.

Beyond these broad community and educational goals, we have the following more concrete goals during SGP Phase 2:

• Expand the geological and geographic scope of samples in our database. Most samples with complete context information (SGP direct entry), and indeed most samples, are Neoproterozoic-Paleozoic in age and from North America (Fig. 4). Younger and older samples, and worldwide sampling, are necessary for accurate analyses through the full swath of Earth history.

• Expand the carbonate geochemical record. Our database structure is appropriate for carbonate data (and indeed, >8000 carbonate samples are already in the database).

However, this goal will require community discussion regarding how best to incorporate methodologies and phase-specific analyses.

• Continue correcting errors in previously entered data. Although we have been as careful as possible during data entry, mistakes are inevitable in a dataset of this size. Paleobiological analyses and basic statistical logic suggest that such mistakes (random error) will not affect results as long as they are not biased (systematic error) [START_REF] Sepkoski | Ten Years in the Library: New Data Confirm Paleontological Patterns[END_REF]. Nonetheless, we would like to present the most accurate results, and we welcome users to notify us of true errors (rather than geologic disagreement) that are found during their database searches.

• Continue developing the SGP search website and API to best serve the sedimentary geochemistry and Earth history communities.

• Expand the community and user group. Anyone who is interested in contributing to the project is welcome, and helping the community grow our data resource is the only requirement to join the SGP Collaborative Team. Details, including contact information and sample submission templates, are available at https://sgp.stanford.edu/. We want SGP to be a hub for deep-time sedimentary geochemical research, and researchers from diverse backgrounds, early-career researchers, and researchers working or studying outside Europe and North America (where the bulk of SGP members reside) are especially invited to become involved.

Echoing this final point, we reiterate that the SGP is a community-oriented research consortium and we welcome suggestions on how to best move towards our shared goals.

Figure captions

Figure 1:

The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is an open, collaborative consortium focused on understanding how the Earth has changed through time through analyses of large sedimentary geochemical datasets.

Figure 2:

Simplified schema showing tables and table relationships in the SGP database (https://ufarrell.github.io/sgp_phase1/ for a detailed description). Tables are grouped according to the kind of information they store. Analytical tables (orange) are from the British Geological Survey model [START_REF] Watson | Open Geoscience Data Models: End of project report[END_REF]. Geographical, geological (green) and sample (red) tables are primarily based on natural history museum databases. 'Housekeeping' tables (purple) record information such as how samples are grouped into projects, where they are stored, and who has contributed contextual information.

Fig. 1 )

 1 Fig. 1), which is an open, community-oriented, database-driven research consortium. The goals of

Figure 3 :

 3 Figure captionsFigure 1: The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is an open, collaborative consortium focused on understanding how the Earth has changed through time through analyses of large sedimentary geochemical datasets.Figure 2:Simplified schema showing tables and table relationships in the SGP database (https://ufarrell.github.io/sgp_phase1/ for a detailed description). Tables are grouped according to the kind of information they store. Analytical tables (orange) are from the British Geological Survey model[START_REF] Watson | Open Geoscience Data Models: End of project report[END_REF]. Geographical, geological (green) and sample (red) tables are primarily based on natural history museum databases. 'Housekeeping' tables (purple) record information such as how samples are grouped into projects, where they are stored, and who has contributed contextual information. Figure 3: Geographic distribution of samples in the Phase 1 dataset, separated by our three main data sources (SGP direct entry, USGS CMIBS, and USGS NGDB).Figure 4: Distribution by age and continent for SGP direct entry data (a). Distribution by age for SGP, USGS CMIBS and USGS NGDB data (a small number of samples (489) with ages >2500 Ma are not included in the figure) (b).

Figure 4 :

 4 Figure captionsFigure 1: The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is an open, collaborative consortium focused on understanding how the Earth has changed through time through analyses of large sedimentary geochemical datasets.Figure 2:Simplified schema showing tables and table relationships in the SGP database (https://ufarrell.github.io/sgp_phase1/ for a detailed description). Tables are grouped according to the kind of information they store. Analytical tables (orange) are from the British Geological Survey model[START_REF] Watson | Open Geoscience Data Models: End of project report[END_REF]. Geographical, geological (green) and sample (red) tables are primarily based on natural history museum databases. 'Housekeeping' tables (purple) record information such as how samples are grouped into projects, where they are stored, and who has contributed contextual information. Figure 3: Geographic distribution of samples in the Phase 1 dataset, separated by our three main data sources (SGP direct entry, USGS CMIBS, and USGS NGDB).Figure 4: Distribution by age and continent for SGP direct entry data (a). Distribution by age for SGP, USGS CMIBS and USGS NGDB data (a small number of samples (489) with ages >2500 Ma are not included in the figure) (b).

Figure 5 :

 5 Figure 5:Representation of lithologies in the Phase 1 dataset. Note that most unclassified samples from SGP direct entry and USGS CMIBS will be fine-grained clastic rocks (e.g., shale) whereas USGS NGDB unclassified samples are more heterogeneous.

Acknowledgements

We thank Sufian Lattouf for developing the initial version of the SGP website, and Kai Lenz, Kassie Sharp, Aaron Cole, Clare Swan, Lyna Kim, and John Freshwaters for computational assistance. We thank Erin Saupe, Itay Halevy, Jordon Hemingway, Minming Cui, Maya Gomes, Matthew Granitto, Alf Lenz, Charles Henderson, Chengsheng Jin, Clint Scott, David Champion,

Paulo Linarde Dantas Mascena, Will Thompson-Butler, and Yu Liu for their contributions to SGP.

We thank the donors of The American Chemical Society Petroleum Research Fund for partial support of SGP website development (61017-ND2). EAS is funded by National Science Foundation grant (NSF) EAR-1922966. BGS authors (JE, PW) publish with permission of the Executive Director of the British Geological Survey, UKRI. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

The authors declare no conflicts of interest.

The Sedimentary Geochemistry and Paleoenvironments Project Keywords: geochemistry, database, Earth history, consortium, website

USGS CMIBS

The data incorporated from USGS CMIBS into the SGP database include 12,797 samples with 409,188 results. The samples are from 45 countries, with 40% from Canada, 27% from the United States, and 13% from Australia. The majority of samples are fine-grained siliciclastic sediments (69% shale, mudstone, siltstone or argillite; Fig. 5). Sixty percent of samples with interpreted ages are Paleozoic, 24% are Mesozoic, 2% are Cenozoic, and 15% are Proterozoic/Archean.

As was the case for USGS NGDB, contextual details, including depositional environment and lowgrade metamorphic bin, are often missing for these samples. However, more detailed geochemical methodological information is available. Each sample in CMIBS has a 'best value' result per analyte, selected from multiple values that were originally available [START_REF] Granitto | Global Geochemical Database for Critical Metals in Black Shales[END_REF]. The choice of 'best value' was made using a rubric which included consideration of the sample weight, the sample 'decomposition' (e.g. full vs. partial acid digestion), the instruments used in the analysis and the detection limits [START_REF] Granitto | Alaska Geochemical Database, Version 2.0 (AGDB2)-Including "best value" data compilations for rock, sediment, soil, mineral, and concentrate sample media[END_REF].

Data Presentation and Access

The SGP search website (sgp-search.io) utilizes an intuitive user interface to query the Phase 1 database via an API. The two main search types are 'samples' and 'analyses,' with 'nhhxrf' simply being a 'samples' search that excludes any handheld XRF (X-ray fluorescence) data. This methodological distinction is made because while handheld XRF data can be accurate for some elements (e.g., Ca, Fe), it is highly inaccurate for many others (e.g., S, Ni) [START_REF] Rowe | The quantification and application of handheld energy-dispersive x-ray fluorescence (ED-XRF) in mudrock chemostratigraphy and geochemistry[END_REF].

Handheld XRF data represent 1% of the total results and 4% of SGP-contributed data; although