Integrative clinical genomics of metastatic cancer

The tumor microenvironment and dendritic cells: Developers of pioneering strategies in colorectal cancer immunotherapy?

Colorectal cancer (CRC) is the world's third most frequent cancer, and both its incidence and fatality rates are rising. Despite various therapeutic approaches, neither its mortality rate nor its recurrence frequency has decreased significantly. Additionally, conventional treatment approaches, such as chemotherapy and radiotherapy, have several side effects and risks for patients with CRC. Accordingly, the need for alternative and effective treatments for CRC patients is critical. Immunotherapy that utilizes dendritic cells (DCs) harnesses the patient's immune system to combat cancer cells effectively. DCs are the most potent antigen-presenting cells (APCs), which play a vital role in generating anti-cancer T cell responses. A significant barrier to the immune system's ability to eliminate CRC is the establishment of a potent immunosuppressive tumor milieu by malignant cells. Since DCs are frequently defective in this milieu, the tumor setting significantly reduces the effectiveness of DC-based therapy. Determining central mechanisms contributing to tumor growth by unraveling and comprehending the interaction between CRC tumor milieu and DCs may lead to new therapeutic approaches. This study aims to review DC biology and discuss its role in T-cell-mediated anti-tumor immunity, as well as to highlight the immunosuppressive effects of the CRC tumor milieu on the function of DCs. We will also highlight the tumor microenvironment (TME)-related factors that interfere with DC function as a possible therapeutic target to enhance DC-based cell therapy efficacy.

The UBA1-STUB1 Axis Mediates Cancer Immune Escape and Resistance to Checkpoint Blockade

SIGNIFICANCE

Our study reveals UBA1 as a predictive biomarker for clinical outcomes in ICB cohorts, mediating cancer immune evasion and ICB resistance. We further highlight JAK1 stabilization as a key mechanism of UBA1 inhibition and nominate the UBA1-STUB1 axis as an immuno-oncology therapeutic target to improve the efficacy of ICB.

SLC26A9 promotes the initiation and progression of breast cancer by activating the PI3K/AKT signaling pathway

SLC26A9 is a member of the Slc26a family of multifunctional anion transporters that function as Cl- channels in the stomach. We reported for the first time that SLC26A9 is involved in gastric tumorigenesis. However, the role of SLC26A9 in breast cancer has not yet been investigated. We first demonstrated that the upregulation of SLC26A9 is associated with the clinicopathological progression and poor prognosis of patients with breast cancer and is positively correlated with HER2 amplification. SLC26A9 alters the proliferation, migration, and invasion potential of breast cancer cells by regulating the PI3K/AKT signaling pathway. SLC26A9 acts as an oncogene in the development of breast cancer. These findings provide valuable insights for the development of future diagnostic and therapeutic strategies for BC.

Biologically relevant integration of transcriptomics profiles from cancer cell lines, patient-derived xenografts, and clinical tumors using deep learning

Cell lines and patient-derived xenografts are essential to cancer research; however, the results derived from such models often lack clinical translatability, as they do not fully recapitulate the complex cancer biology. Identifying preclinical models that sufficiently resemble the biological characteristics of clinical tumors across different cancers is critically important. Here, we developed MOBER, Multi-Origin Batch Effect Remover method, to simultaneously extract biologically meaningful embeddings while removing confounder information. Applying MOBER on 932 cancer cell lines, 434 patient-derived tumor xenografts, and 11,159 clinical tumors, we identified preclinical models with greatest transcriptional fidelity to clinical tumors and models that are transcriptionally unrepresentative of their respective clinical tumors. MOBER allows for transformation of transcriptional profiles of preclinical models to resemble the ones of clinical tumors and, therefore, can be used to improve the clinical translation of insights gained from preclinical models. MOBER is a versatile batch effect removal method applicable to diverse transcriptomic datasets, enabling integration of multiple datasets simultaneously.

Comprehensive analysis reveals PLK3 as a promising immune target and prognostic indicator in glioma

Background

PLK3, which played an important role in cell cycle progression and stress response, was identified as highly expressed in various carcinomas. However, the functions, molecular characteristics, and prognostic value of PLK3 in glioma remained unexplored.

Methods

We analyzed PLK3 expression in glioma samples from multiple databases. Both overexpression and knockdown of Plk3 were performed to investigate tumor cell growth in glioma, and the transplanted glioma mouse model demonstrated the role of Plk3 on tumor progression. Immunohistochemistry was conducted to detect PLK3 expression and immune cell infiltration. The trans-well assay for PLK3 on the immune cells recruitment was also determined. Additionally, we further evaluated the correlation between PLK3 and PD-1/PD-L1 as well as other immune checkpoints.

Results

We found that an increased level of PLK3 was associated with malignancy and poor prognosis of glioma, and further validated that PLK3 promoted glioma progression. PLK3 also played a crucial role in immune response and was involved in Tcell immune suppression. Specifically, we revealed that CD8+ and CD4+ Tcell infiltration was decreased in Plk3 overexpressed xenografts. Furthermore, it was predicted that PLK3 was synergistic with other checkpoint members in glioma. In general, high expression of PLK3 was associated with a malignant process and poor prognosis in glioma patients.

Conclusion

Our findings indicated that PLK3 expression level was highly correlated to the malignancy of gliomas, and we validated that PLK3 could promote the GBM progress in vitro and in vivo. Furthermore, PLK3 played important roles in Tcell and neutrophil immune response in glioma. Besides, the conspicuous association between PLK3 and other immune checkpoints was also observed. Crucially, high-level PLK3 expression was revealed to be related to poor clinical prognosis. These results demonstrated that PLK3 may serve as a prognostic biomarker and a potential target for glioma.

Cancer vaccines: platforms and current progress

Cancer vaccines, crucial in the immunotherapeutic landscape, are bifurcated into preventive and therapeutic types, both integral to combating oncogenesis. Preventive cancer vaccines, like those against HPV and HBV, reduce the incidence of virus-associated cancers, while therapeutic cancer vaccines aim to activate dendritic cells and cytotoxic T lymphocytes for durable anti-tumor immunity. Recent advancements in vaccine platforms, such as synthetic peptides, mRNA, DNA, cellular, and nano-vaccines, have enhanced antigen presentation and immune activation. Despite the US Food and Drug Administration approval for several vaccines, the full therapeutic potential remains unrealized due to challenges such as antigen selection, tumor-mediated immunosuppression, and optimization of delivery systems. This review provides a comprehensive analysis of the aims and implications of preventive and therapeutic cancer vaccine, the innovative discovery of neoantigens enhancing vaccine specificity, and the latest strides in vaccine delivery platforms. It also critically evaluates the role of adjuvants in enhancing immunogenicity and mitigating the immunosuppressive tumor microenvironment. The review further examines the synergistic potential of combining cancer vaccines with other therapies, such as chemotherapy, radiotherapy, and immune checkpoint inhibitors, to improve therapeutic outcomes. Overcoming barriers such as effective antigen identification, immunosuppressive microenvironments, and adverse effects is critical for advancing vaccine development. By addressing these challenges, cancer vaccines can offer significant improvements in patient outcomes and broaden the scope of personalized cancer immunotherapy.

SARCP, a Clinical Next-Generation Sequencing Assay for the Detection of Gene Fusions in Sarcomas: A Description of the First 652 Cases

An amplicon-based targeted next-generation sequencing (NGS) assay for the detection of gene fusions in sarcomas was developed, validated, and implemented. This assay can detect fusions in targeted regions of 138 genes and BCOR internal tandem duplications. This study reviews our experience with testing on the first 652 patients analyzed. Gene fusions were detected in 238 (36.5%) of 652 cases, including 83 distinct fusions in the 238 fusion-positive cases, 10 of which had not been previously described. Among the 238 fusion-positive cases, the results assisted in establishing a diagnosis for 137 (58%) cases, confirmed a suspected diagnosis in 66 (28%) cases, changed a suspected diagnosis in 25 (10%) cases, and were novel fusions with unknown clinical significance in 10 (4%) cases. Twenty-six cases had gene fusions (ALK, ROS1, NTRK1, NTRK3, and COL1A1::PDGFB) for which there are targetable therapies. BCOR internal tandem duplications were identified in 6 (1.2%) of 485 patients. Among the 138 genes in the panel, 66 were involved in one or more fusions, and 72 were not involved in any fusions. There was little overlap between the genes involved as 5'-partners (31 different genes) and 3'-partners (37 different genes). This study shows the clinical utility of a next-generation sequencing gene fusion detection assay for the diagnosis and treatment of sarcomas.

Liver cancer multiomics reveals diverse protein kinase A disruptions convergently produce fibrolamellar hepatocellular carcinoma

Fibrolamellar Hepatocellular Carcinoma (FLC) is a rare liver cancer characterized by a fusion oncokinase of the genes DNAJB1 and PRKACA, the catalytic subunit of protein kinase A (PKA). A few FLC-like tumors have been reported showing other alterations involving PKA. To better understand FLC pathogenesis and the relationships among FLC, FLC-like, and other liver tumors, we performed a massive multi-omics analysis. RNA-seq data of 1412 liver tumors from FLC, hepatocellular carcinoma, hepatoblastoma and intrahepatic cholangiocarcinoma are analyzed, obtaining transcriptomic signatures unrestricted by experimental processing methods. These signatures reveal which dysregulations are unique to specific tumors and which are common to all liver cancers. Moreover, the transcriptomic FLC signature identifies a unifying phenotype for all FLC tumors regardless of how PKA was activated. We study this signature at multi-omics and single-cell levels in the first spatial transcriptomic characterization of FLC, identifying the contribution of tumor, normal, stromal, and infiltrating immune cells. Additionally, we study FLC metastases, finding small differences from the primary tumors.

Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study

PURPOSE

Renal cell carcinoma (RCC), exhibiting remarkable heterogeneity, can be highly infiltrated by regulatory T cells (Tregs). However, the relationship between Treg and the heterogeneity of RCC remains to be explored.

METHODS

We acquired single-cell RNA-seq profiles and 537 bulk RNA-seq profiles of TCGA-KIRC cohort. Through clustering, monocle2 pseudotime and prognostic analyses, we identified Treg states-related prognostic genes (TSRPGs), then constructing the RCC Treg states-related prognostic classification (RCC-TSC). We also explored its prognostic significance and multi-omics landmarks. Additionally, we utilized correlation analysis to establish regulatory networks, and predicted candidate inhibitors. More importantly, in Xinhua cohort of 370 patients with kidney neoplasm, we used immunohistochemical (IHC) staining for classification, then employing statistical analyses including Chi-square tests and multivariate Cox proportional hazards regression analysis to explore its clinical relevance.

RESULTS

We defined 44 TSRPGs in four different monocle states, and identified high immune infiltration RCC (HIRC, LAG3+, Mki67+) as the highly exhausted subtype with the worst prognosis in RCC-TSC (p < 0.001). BATF-LAG3-immune cells axis might be its underlying metastasis-related mechanism. Immunotherapy and inhibitors including sunitinib potentially conferred best therapeutic effects for HIRC. Furthermore, we successfully validated HIRC subtype as an independent prognostic factor within the Xinhua cohort (OS, HR = 16.68, 95% CI = 1.88-148.1, p = 0.011; PFS, HR = 4.43, 95% CI = 1.55-12.6, p = 0.005).

CONCLUSION

Through integrated bioinformatics analysis and a large-sample retrospective clinical study, we successfully established RCC-TSC and a diagnostic kit, which could stratify RCC patients with different prognosis and to guide personalized treatment.

Germline loss-of-function variant in the E3 ubiquitin ligase TRAF2 in a young adult patient with medulloblastoma: a case report

We identified a rare heterozygous germline loss-of-function variant in the tumor necrosis factor receptor-associated factor 2 (TRAF2) in a young adult patient diagnosed with medulloblastoma. This variant is located within the TRAF-C domain of the E3 ubiquitin ligase protein and is predicted to diminish the binding affinity of TRAF2 to upstream receptors and associated adaptor proteins. Integrative genomics revealed a biallelic loss of TRAF2 via partial copy-neutral loss-of-heterozygosity of 9q in the medulloblastoma genome. We further performed comparative analysis with an in-house cohort of 20 medulloblastomas sequenced using the same platform, revealing an atypical molecular profile of the TRAF2-associated medulloblastoma. Our research adds to the expanding catalog of genetic tumor syndromes that increase the susceptibility of carriers to MB.

The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

Itaconate transporter SLC13A3 impairs tumor immunity via endowing ferroptosis resistance

Immune checkpoint blockade (ICB) triggers tumor ferroptosis. However, most patients are unresponsive to ICB. Tumors might evade ferroptosis in the tumor microenvironment (TME). Here, we discover SLC13A3 is an itaconate transporter in tumor cells and endows tumor ferroptosis resistance, diminishing tumor immunity and ICB efficacy. Mechanistically, tumor cells uptake itaconate via SLC13A3 from tumor-associated macrophages (TAMs), thereby activating the NRF2-SLC7A11 pathway and escaping from immune-mediated ferroptosis. Structural modeling and molecular docking analysis identify a functional inhibitor for SLC13A3 (SLC13A3i). Deletion of ACOD1 (an essential enzyme for itaconate synthesis) in macrophages, genetic ablation of SLC13A3 in tumors, or treatment with SLC13A3i sensitize tumors to ferroptosis, curb tumor progression, and bolster ICB effectiveness. Thus, we identify the interplay between tumors and TAMs via the SLC13A3-itaconate-NRF2-SLC7A11 axis as a previously unknown immune ferroptosis resistant mechanism in the TME and SLC13A3 as a promising immunometabolic target for treating SLC13A3+ cancer.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to their target tissues remains a fundamental challenge. To address this, we assessed whether primary and metastatic tumors more closely resemble their tissues of origin or target tissues in terms of gene expression. We analyzed expression profiles from multiple cancer types and normal tissues, including single-cell and bulk RNA sequencing data from both paired and unpaired patient cohorts. Primary tumors were overall more transcriptomically similar to their tissues of origin, while metastases shifted toward their target tissues. However, pathway-level analysis highlighted critical metabolic and immune transcriptomic changes toward target tissues during metastasis in both primary and metastatic tumors. In addition, primary tumors exhibited higher activity in cancer hallmarks such as "Activating Invasion and Metastasis" when compared to metastases. This comprehensive analysis provides a transcriptome-wide view of the processes through which cancer tumors adapt to their metastatic environments before and after metastasis.

Phase II trial of multi-tyrosine kinase inhibitor ESK981 in combination with PD-1 inhibitor nivolumab in patients with metastatic castration-resistant prostate cancer

Increasing the response rates of immune checkpoint inhibitors in patients with metastatic castration-resistant prostate cancer (mCRPC) presents a significant challenge. ESK981 is a multi-tyrosine kinase and PIKfyve lipid kinase inhibitor that augments immunotherapeutic responses. In this phase II study, ESK981 was combined with the PD-1 blocking monoclonal antibody nivolumab to test for potentially improved response rates in patients with mCRPC who have progressed on androgen receptor (AR)-targeted agents and chemotherapy. Eligible patients received ESK981 orally once daily for five consecutive days, followed by a two-day break. Patients were also treated with nivolumab intravenously on Day 1 of each 28-day cycle. The primary endpoints were a 50% reduction in prostate-specific antigen (PSA50), and safety. Secondary endpoints included radiographic progression free survival (rPFS) and overall survival (OS). Additional investigations included whole exome sequencing in patients. Ten patients were enrolled. The maximum PSA decline from baseline of 14% was achieved in only one patient. Grade 3 treatment-related adverse events (AEs) included fatigue, anemia, and lymphopenia. There were no Grade 4 events. The median rPFS was 3.7 months (95% CI, 1.6-8.4). The median OS was 9.6 months (95% CI, 1.8-22.4). The study was terminated due to futility after 10 patients. Whole exome sequencing identified AR amplification in 63% of patients (5/8). ESK981 + nivolumab showed no antitumor activity in patients with AR-positive (AR+) mCRPC. Further evaluation of ESK981 combined with the PD-1 inhibitor nivolumab in AR + mCRPC patients is not warranted. (Trial registration: ClinicalTrials.gov NCT04159896. Registration date: November 12, 2019.).

Paired CRISPR screens to map gene regulation in cis and trans

Recent massively-parallel approaches to decipher gene regulatory circuits have focused on the discovery of either cis -regulatory elements (CREs) or trans -acting factors. Here, we develop a scalable approach that pairs cis - and trans -regulatory CRISPR screens to systematically dissect how the key immune checkpoint PD-L1 is regulated. In human pancreatic ductal adenocarcinoma (PDAC) cells, we tile the PD-L1 locus using ∼25,000 CRISPR perturbations in constitutive and IFNγ-stimulated conditions. We discover 67 enhancer- or repressor-like CREs and show that distal CREs tend to contact the promoter of PD-L1 and related genes. Next, we measure how loss of all ∼2,000 transcription factors (TFs) in the human genome impacts PD-L1 expression and, using this, we link specific TFs to individual CREs and reveal novel PD-L1 regulatory circuits. For one of these regulatory circuits, we confirm the binding of predicted trans -factors (SRF and BPTF) using CUT&RUN and show that loss of either the CRE or TFs potentiates the anti-cancer activity of primary T cells engineered with a chimeric antigen receptor. Finally, we show that expression of these TFs correlates with PD-L1 expression in vivo in primary PDAC tumors and that somatic mutations in TFs can alter response and overall survival in immune checkpoint blockade-treated patients. Taken together, our approach establishes a generalizable toolkit for decoding the regulatory landscape of any gene or locus in the human genome, yielding insights into gene regulation and clinical impact.

Oxidative Stress and Cancer Therapy: Controlling Cancer Cells Using Reactive Oxygen Species

Cancer is a multifaceted disease influenced by various mechanisms, including the generation of reactive oxygen species (ROS), which have a paradoxical role in both promoting cancer progression and serving as targets for therapeutic interventions. At low concentrations, ROS serve as signaling agents that enhance cancer cell proliferation, migration, and resistance to drugs. However, at elevated levels, ROS induce oxidative stress, causing damage to biomolecules and leading to cell death. Cancer cells have developed mechanisms to manage ROS levels, including activating pathways such as NRF2, NF-κB, and PI3K/Akt. This review explores the relationship between ROS and cancer, focusing on cell death mechanisms like apoptosis, ferroptosis, and autophagy, highlighting the potential therapeutic strategies that exploit ROS to target cancer cells.

Prevention of liver metastasis via the pharmacological suppression of AMIGO2 expression in tumor cells

AMIGO2 adheres to liver endothelium and induces liver metastasis. We revealed that genetically altering AMIGO2 expression in tumor cells affects their liver metastatic potential, depending on the AMIGO2 expression level. The aim of this study was to prevent liver metastasis by pharmacologically suppressing AMIGO2 expression. For screening, we used the mouse LV12 cells because of their affinity to adhere to liver endothelium and metastasize the liver owing to elevated AMIGO2 expression. Of the 285 compounds tested, 17 reduced AMIGO2 mRNA expression. We subsequently screened for compounds that inhibited tumor cell adhesion to liver endothelium and identified five compounds that inhibit three signaling pathways (MEK, JAK, and JNK). Treatment with these compounds inhibited liver metastasis of LV12 cells. Next, we used clinically available signal inhibitors (MEK inhibitor trametinib, JAK inhibitor ruxolitinib, and JNK inhibitor SP600125), and found that ruxolitinib inhibits AMIGO2 expression more stably. Furthermore, ruxolitinib inhibited the adhesion of LV12 cells to liver endothelium and suppressed liver metastasis. Using the MKN45 gastric cancer cells, we confirmed that ruxolitinib could prevent liver metastasis of human cancer cells. These results demonstrate that pharmacological inhibition of AMIGO2 expression in tumor cells is a promising novel strategy to prevent and control liver metastasis.

Hope for Others: Research Results from the University of Pittsburgh Rapid Autopsy Program for Breast Cancer

Breast cancer affects 1/8 of women throughout their lifetimes, with 90% of cancer deaths being caused by metastasis. However, metastasis poses unique challenges to research, as complex changes in the microenvironment in different metastatic sites and difficulty obtaining tissue for study hinder the ability to examine in depth the changes that occur during metastasis. Rapid autopsy programs thus fill a unique need in advancing metastasis research. Here, we describe our protocol and processes for establishing and improving the US-based Hope for OTHERS (Our Tissue Helping Enhance Research and Science) program for organ donation in metastatic breast cancer. Our results reveal key logistical and protocol improvements that are uniquely beneficial to certain programs based on identifiable features, such as working closely with patient advocates, methods to rescue RNA quality in cases where tissue quality may degrade due to time delays, as well as guidelines and future expansions of our program with new research and novel research findings in patient outcomes, metastatic phylogeny, living model development and more.

The SRC-family serves as a therapeutic target in triple negative breast cancer with acquired resistance to chemotherapy

BACKGROUND

Resistance to chemotherapy, combined with heterogeneity among resistant tumors, represents a significant challenge in the clinical management of triple negative breast cancer (TNBC). By dissecting molecular pathways associated with treatment resistance, we sought to define patient sub-groups and actionable targets for next-line treatment.

METHODS

Bulk RNA sequencing and reverse phase protein array profiling were performed on isogenic patient-derived xenografts (PDX) representing paclitaxel-sensitive and -resistant tumors. Pathways identified as upregulated in the resistant model were further explored as targets in PDX explants. Their clinical relevance was assessed in two distinct patient cohorts (NeoAva and MET500).

RESULTS

Increased activity in signaling pathways involving SRC-family kinases (SFKs)- and MAPK/ERK was found in treatment resistant PDX, with targeted inhibitors being significantly more potent in resistant tumors. Up-regulation of SFKs- and MAPK/ERK-pathways was also detected in a sub-group of chemoresistant patients after neoadjuvant treatment. Furthermore, High SFK expression (of either SRC, FYN and/or YES1) was detected in metastatic lesions of TNBC patients with fast progressing disease (median disease-free interval 27 vs 105 months).

CONCLUSIONS

Upregulation of SFK-signaling is found in a subset of chemoresistant tumors and is persistent in metastatic lesions. Based on pre-clinical results, these patients may respond favorably to treatment targeting SFKs.

Clinical proteomics towards multiomics in cancer

Recent technological advancements in mass spectrometry (MS)-based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS-based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re-examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi-omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets.

Squamoid Eccrine Ductal Carcinoma Displays Ultraviolet Mutations and Intermediate Gene Expression Relative to Squamous Cell Carcinoma, Microcystic Adnexal Carcinoma, and Porocarcinoma

Squamoid eccrine ductal carcinoma is a rare infiltrative tumor with morphologic features intermediate between squamous cell carcinoma (SCC) and sweat gland carcinomas such as microcystic adnexal carcinoma. Although currently classified as a sweat gland carcinoma, it has been debated whether squamoid eccrine ductal carcinoma is better classified as a variant of SCC. Furthermore, therapeutic options for patients with advanced disease are lacking. Here, we describe clinicopathologic features of a cohort of 15 squamoid eccrine ductal carcinomas from 14 unique patients, with next-generation sequencing DNA profiling for 12 cases. UV signature mutations were the dominant signature in the majority of cases. TP53 mutations were the most highly recurrent specific gene alteration, followed by mutations in NOTCH genes. Recurrent mutations in driver oncogenes were not identified. By unsupervised comparison of global transcriptome profiles in squamoid eccrine ductal carcinoma (n = 7) to SCC (n = 10), porocarcinoma (n = 4), and microcystic adnexal carcinoma (n = 4), squamoid eccrine ductal carcinomas displayed an intermediate phenotype between SCC and sweat gland tumors. Squamoid eccrine ductal carcinoma displayed significantly higher expression of 364 genes (including certain eccrine markers) and significantly lower expression of 525 genes compared with other groups. Our findings support the classification of squamoid eccrine ductal carcinoma as a carcinoma with intermediate features between SCC and sweat gland carcinoma.

Developmental-status-aware transcriptional decomposition establishes a cell state panorama of human cancers

BACKGROUND

Cancer cells evolve under unique functional adaptations that unlock transcriptional programs embedded in adult stem and progenitor-like cells for progression, metastasis, and therapeutic resistance. However, it remains challenging to quantify the stemness-aware cell state of a tumor based on its gene expression profile.

METHODS

We develop a developmental-status-aware transcriptional decomposition strategy using single-cell RNA-sequencing-derived tissue-specific fetal and adult cell signatures as anchors. We apply our method to various biological contexts, including developing human organs, adult human tissues, experimentally induced differentiation cultures, and bulk human tumors, to benchmark its performance and to reveal novel biology of entangled developmental signaling in oncogenic processes.

RESULTS

Our strategy successfully captures complex dynamics in developmental tissue bulks, reveals remarkable cellular heterogeneity in adult tissues, and resolves the ambiguity of cell identities in in vitro transformations. Applying it to large patient cohorts of bulk RNA-seq, we identify clinically relevant cell-of-origin patterns and observe that decomposed fetal cell signals significantly increase in tumors versus normal tissues and metastases versus primary tumors. Across cancer types, the inferred fetal-state strength outperforms published stemness indices in predicting patient survival and confers substantially improved predictive power for therapeutic responses.

CONCLUSIONS

Our study not only provides a general approach to quantifying developmental-status-aware cell states of bulk samples but also constructs an information-rich, biologically interpretable, cell-state panorama of human cancers, enabling diverse translational applications.

Comprehensive Characterization of the Integrin Family Across 32 Cancer Types

Integrin genes are widely involved in tumorigenesis. Yet, a comprehensive characterization of integrin family members and their interactome at the pan-cancer level is lacking. Here, we systematically analyzed integrin family in approximately 10,000 tumors across 32 cancer types. Globally, integrins represent a frequently altered and misexpressed pathway, with alteration and dysregulation overall being protumorigenic. Expression dysregulation, better than mutational landscape, of integrin family successfully identifies a subgroup of aggressive tumors with a high level of proliferation and stemness. The results reveal that several molecular mechanisms collectively regulate integrin expression in a context-dependent manner. For potential clinical usage, we constructed a weighted scoring system, integrinScore, to measure integrin signaling patterns in individual tumors. Remarkably, integrinScore was consistently correlated with predefined molecular subtypes in multiple cancers, with integrinScore-high tumors being more aggressive. Importantly, integrinScore was cancer-dependent and closely associated with proliferation, stemness, tumor microenvironment, metastasis, and immune signatures. IntegrinScore also predicted patients' response to immunotherapy. By mining drug databases, we unraveled an array of compounds that may modulate integrin signaling. Finally, we built a user-friendly database, Pan-cancer Integrin Explorer (PIExplorer; http://computationalbiology.cn/PIExplorer), to facilitate researchers to explore integrin-related knowledge. Collectively, we provide a comprehensive characterization of integrins across cancers and offer gene-specific and cancer-specific rationales for developing integrin-targeted therapy.

CDK12 loss drives prostate cancer progression, transcription-replication conflicts, and synthetic lethality with paralog CDK13

Biallelic loss of cyclin-dependent kinase 12 (CDK12) defines a metastatic castration-resistant prostate cancer (mCRPC) subtype. It remains unclear, however, whether CDK12 loss drives prostate cancer (PCa) development or uncovers pharmacologic vulnerabilities. Here, we show Cdk12 ablation in murine prostate epithelium is sufficient to induce preneoplastic lesions with lymphocytic infiltration. In allograft-based CRISPR screening, Cdk12 loss associates positively with Trp53 inactivation but negatively with Pten inactivation. Moreover, concurrent Cdk12/Trp53 ablation promotes proliferation of prostate-derived organoids, while Cdk12 knockout in Pten-null mice abrogates prostate tumor growth. In syngeneic systems, Cdk12/Trp53-null allografts exhibit luminal morphology and immune checkpoint blockade sensitivity. Mechanistically, Cdk12 inactivation mediates genomic instability by inducing transcription-replication conflicts. Strikingly, CDK12-mutant organoids and patient-derived xenografts are sensitive to inhibition or degradation of the paralog kinase, CDK13. We therein establish CDK12 as a bona fide tumor suppressor, mechanistically define how CDK12 inactivation causes genomic instability, and advance a therapeutic strategy for CDK12-mutant mCRPC.

FANCA promotes lung adenocarcinoma progression and is a potential target for epitope vaccine immunotherapy

BACKGROUND

FANCA mutations have been detected in a variety of cancers and found to be pro-carcinogenic. However, no functional studies have been identified regarding the involvement of FANCA in the occurrence and the immune response of LUAD.

METHODS

The mRNA expression and overall survival rates of FANCA were evaluated by the TIMER, PrognoScan and TCGA database in LUAD tissues, and FANCA expression was further validated by clinical serum samples using ELISA. The correlation between FANCA and immune infiltration level was investigated via TISIDB database and CIBERSORT algorithm. The Kaplan-Meier plotter was used to further evaluate the prognostic value based on the expression levels of FANCA in related immune cells. Then, the influence of FANCA knockout on the proliferation, migration, and invasion of A549 and H1299 cells was validated using CCK8, cloning formation, and Transwell assays. Subsequently, HLA-A2-restricted FANCA antigenic peptides were predicted and synthesized by NetMHC4.0 and SYFPEITHI, and DCs were induced and cultured in vitro. Finally, DCs loaded with HLA-A2-restricted FANCA antigenic peptides were co-cultured with autologous peripheral blood lymphocyte to generate specific CTLs. The killing effects of different CTLs on LUAD cells were studied.

RESULTS

The results showed that high levels of FANCA in patients with LUAD were significantly correlated with worse OS survival, which was correlated with age, clinical stage, pathological T stage, M stage, and N stage in LUAD. Knockdown of FANCA in A549 and H1299 cells significantly inhibited proliferation, metastasis, and invasion in vitro. In addition, FANCA was significantly related to immune infiltrate, genomic alterations and TMB. FANCA expression infuenced the prognosis of LUAD patients by directly affecting immune cell infltration. Finally, HLA-A2-restricted FANCA antigenic peptides were synthesized. And FANCA 146-154 (SLLEFAQYL) antigenic peptide exhibit a stronger affinity for DCs, and induce CTLs to produce stronger targeted killing ability for LUAD cells at an effector-to-target ratio of 40:1.

CONCLUSION

These results demonstrated that the elevation of FANCA promotes malignant phenotype of LUAD, and the potential peptide P2 (SLLEFAQYL) derived from FANCA may be used as an epitope vaccine for the treatment of LUAD.

Phase II trial of multi-kinase inhibitor ESK981 in patients with metastatic castration-resistant prostate cancer

ESK981 is a potent tyrosine kinase and PIKfyve lipid kinase inhibitor. This phase II trial evaluated the efficacy of ESK981 as a single agent in patients with androgen receptor-positive (AR +) metastatic castration-resistant prostate cancer (mCRPC). Eligible patients had mCRPC with progression on AR-targeted agents and without prior chemotherapy treatment. Each patient received 160 mg ESK981 once daily for 5 days per week for 4 weeks per cycle (except for an adverse event (AE) occurrence). The primary endpoints were a 50% reduction in prostate-specific antigen (PSA50), and safety. Secondary endpoints included the time and the duration of PSA response, PSA progression rates, PSA progression free survival (PFS) and overall survival (OS). Exploratory investigations included whole exome sequencing in patients before treatment, and morphological evaluation of biopsy samples pre- and post-treatment. PSA was evaluated in 13 patients. Only one patient (7.7% two-sided 95% Wilson CI (0.4%, 33.3%)) experienced a reduction in their PSA levels by 50% or more. The most common grade 3 treatment-related AEs were cardiac disorders, diarrhea, hypertension, alanine transaminase and aspartate transaminase elevations. No grade 4-5 events occurred. Median PFS was 1.8 months, and median OS was 12.1 months. Peripheral immune cells showed increased T cell activation and cytokine production in two patients who received 12-weeks of ESK981. Although relatively well tolerated, ESK981 alone showed no anti-tumor activity in patients with AR + mCRPC and its further evaluation as a single agent in AR + mCRPC is not warranted. (Trial registration: ClinicalTrials.gov, NCT03456804. Registration date: March 7, 2018).

TG-IGF1R: A Novel Receptor Tyrosine Kinase Fusion Oncogene in Pediatric Thyroid Cancer

Background: Receptor tyrosine kinase (RTK) fusions of RET, NTRK1/3, and ALK are enriched among pediatric thyroid cancer patients with metastatic and persistent disease, and their oncoproteins represent attractive drug targets. Methods: We performed RNA-sequencing in a papillary thyroid cancer (PTC) lacking other frequent driver alterations. Results: We report a novel RTK fusion, TG-insulin-like growth factor 1 receptor gene (IGF1R), in a 17-year-old female patient with angioinvasive follicular variant PTC. The in-frame fusion protein preserves the cholinesterase-like domain of TG with dimerization properties and the transmembrane and kinase domain of IGF1R. The tumor sample shows increased IGF1R mRNA expression and tyrosine kinase phosphorylation, augmentation of Mitogen activated protein kinase (MAPK) transcriptional output genes, and decreased NIS levels. Conclusions: We reveal a novel targetable kinase fusion oncogene in thyroid cancer which is not incorporated in different thyroid-specific sequencing panels. The integration of IGF1R fusion screening in the next versions of thyroid-specific targeted next-generation sequencing panels may be beneficial to thyroid cancer patients.

Exploring the molecular landscape of cancer of unknown primary: A comparative analysis with other metastatic cancers

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well-characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune-related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor-infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

Cell Senescence and the Genetics of Melanoma Development

Cutaneous malignant melanoma is an aggressive skin cancer with an approximate lifetime risk of 1 in 38 in the UK. While exposure to ultraviolet radiation is a key environmental risk factor for melanoma, up to ~10% of patients report a family history of melanoma, and ~1% have a strong family history. The understanding of causal mutations in melanoma has been critical to the development of novel targeted therapies that have contributed to improved outcomes for late-stage patients. Here, we review current knowledge of the genes affected by familial melanoma mutations and their partial overlap with driver genes commonly mutated in sporadic melanoma development. One theme linking a set of susceptibility loci/genes is the regulation of skin pigmentation and suntanning. The largest functional set of susceptibility variants, typically with high penetrance, includes CDKN2A, RB1, and telomerase reverse transcriptase (TERT) mutations, associated with attenuation of cell senescence. We discuss the mechanisms of action of these gene sets in the biology and progression of nevi and melanoma.

A novel gene signature based on endoplasmic reticulum stress for predicting prognosis in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) remains one of the most common human cancers, the death cases induced by HCC are increasing these years. Endoplasmic reticulum stress (ERS) occurs when misfolded proteins cannot be disposed of properly. It is reported that ERS plays a crucial role in the pathogenesis of human malignant tumors. The aim of this study is to construct a novel gene signature based on ERS for predicting prognosis in HCC.

Methods

The data of HCC patients were downloaded from public databases. The Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed to construct ERS-related gene signature. The cases were divided into high- and low-risk groups based on the ERS-related gene signature in The Cancer Genome Atlas (TCGA) cohort. Subsequently, the differences in messenger ribonucleic acid (mRNA) expression patterns, immune status, tumor mutation burden (TMB) and copy number variants (CNV) were investigated between high- and low-risk groups. Then, a predictive nomogram according to the ERS-related gene signature and clinicopathological variables was established. At last, we explored the biological functions of TMX1 which had the biggest coefficient and we investigated the effect of BRSK2 on apoptosis in HCC.

Results

In our study, a 9-gene ERS-related gene signature was constructed. The results showed that patients in the low-risk group had a better prognosis than the high-risk group patients. The results of receiver operating characteristic (ROC) curves revealed that the area under the curve (AUC) was 0.784 at 1 year, 0.780 at 2 years, 0.793 at 3 years in the training set. While in validation cohort, this index was 0.694 at 1 year, 0.622 at 2 years, 0.613 at 3 years respectively. The analysis of immune status revealed an immunosuppressive microenvironment in the high-risk group. The analysis of TMB and CNV revealed that the high-risk group patients had a higher genomic mutation frequency. In Univariate Cox regression analysis, the hazard ratio of RiskScore was 2.718 [95% confidence interval (CI): 2.173-3.399]. In Multivariate Cox regression analysis, the hazard ratio of RiskScore was 2.422 (95% CI: 1.805-3.25). Then, we established a nomogram according to the RiskScore and Eastern Cooperative Oncology Group performance status. The AUCs of the nomogram were 0.851 at 1 year, 0.860 at 2 years, and 0.866 at 3 years. At last, we found that TMX1 knockdown can inhibit the proliferation and migration of Huh7 and HepG2 cells. In addition, BRSK2 knockdown could promote the apoptosis induced by ERS.

Conclusions

In our study, a novel ERS-related gene signature was constructed to predict the prognosis of HCC patients. In addition, TMX1 and BRSK2 could promote the progression of HCC. This study may provide a new understanding for HCC.

Mediating kinase activity in Ras-mutant cancer: potential for an individualised approach?

It is widely acknowledged that there is a considerable number of oncogenic mutations within the Ras superfamily of small GTPases which are the driving force behind a multitude of cancers. Ras proteins mediate a plethora of kinase pathways, including the MAPK, PI3K, and Ral pathways. Since Ras was considered undruggable until recently, pharmacological targeting of pathways downstream of Ras has been attempted to varying success, though drug resistance has often proven an issue. Nuances between kinase pathway activation in the presence of various Ras mutants are thought to contribute to the resistance, however, the reasoning behind activation of different pathways in different Ras mutational contexts is yet to be fully elucidated. Indeed, such disparities often depend on cancer type and disease progression. However, we are in a revolutionary age of Ras mutant targeted therapy, with direct-targeting KRAS-G12C inhibitors revolutionising the field and achieving FDA-approval in recent years. However, these are only beneficial in a subset of patients. Approximately 90% of Ras-mutant cancers are not KRAS-G12C mutant, and therefore raises the question as to whether other distinct amino acid substitutions within Ras may one day be targetable in a similar manner, and indeed whether better understanding of the downstream pathways these various mutants activate could further improve therapy. Here, we discuss the favouring of kinase pathways across an array of Ras-mutant oncogenic contexts and assess recent advances in pharmacological targeting of various Ras mutants. Ultimately, we will examine the utility of individualised pharmacological approaches to Ras-mediated cancer.

Non-Negative Matrix Tri-Factorization for Representation Learning in Multi-Omics Datasets with Applications to Drug Repurposing and Selection

The vast corpus of heterogeneous biomedical data stored in databases, ontologies, and terminologies presents a unique opportunity for drug design. Integrating and fusing these sources is essential to develop data representations that can be analyzed using artificial intelligence methods to generate novel drug candidates or hypotheses. Here, we propose Non-Negative Matrix Tri-Factorization as an invaluable tool for integrating and fusing data, as well as for representation learning. Additionally, we demonstrate how representations learned by Non-Negative Matrix Tri-Factorization can effectively be utilized by traditional artificial intelligence methods. While this approach is domain-agnostic and applicable to any field with vast amounts of structured and semi-structured data, we apply it specifically to computational pharmacology and drug repurposing. This field is poised to benefit significantly from artificial intelligence, particularly in personalized medicine. We conducted extensive experiments to evaluate the performance of the proposed method, yielding exciting results, particularly compared to traditional methods. Novel drug-target predictions have also been validated in the literature, further confirming their validity. Additionally, we tested our method to predict drug synergism, where constructing a classical matrix dataset is challenging. The method demonstrated great flexibility, suggesting its applicability to a wide range of tasks in drug design and discovery.

Radiomic-based prediction of lesion-specific systemic treatment response in metastatic disease

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 4.5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.70 for the most precise model (FDR = 0.05). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

Zeb1 mediates EMT/plasticity-associated ferroptosis sensitivity in cancer cells by regulating lipogenic enzyme expression and phospholipid composition

Therapy resistance and metastasis, the most fatal steps in cancer, are often triggered by a (partial) activation of the epithelial-mesenchymal transition (EMT) programme. A mesenchymal phenotype predisposes to ferroptosis, a cell death pathway exerted by an iron and oxygen-radical-mediated peroxidation of phospholipids containing polyunsaturated fatty acids. We here show that various forms of EMT activation, including TGFβ stimulation and acquired therapy resistance, increase ferroptosis susceptibility in cancer cells, which depends on the EMT transcription factor Zeb1. We demonstrate that Zeb1 increases the ratio of phospholipids containing pro-ferroptotic polyunsaturated fatty acids over cyto-protective monounsaturated fatty acids by modulating the differential expression of the underlying crucial enzymes stearoyl-Co-A desaturase 1 (SCD), fatty acid synthase (FASN), fatty acid desaturase 2 (FADS2), elongation of very long-chain fatty acid 5 (ELOVL5) and long-chain acyl-CoA synthetase 4 (ACSL4). Pharmacological inhibition of selected lipogenic enzymes (SCD and FADS2) allows the manipulation of ferroptosis sensitivity preferentially in high-Zeb1-expressing cancer cells. Our data are of potential translational relevance and suggest a combination of ferroptosis activators and SCD inhibitors for the treatment of aggressive cancers expressing high Zeb1.

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Crosstalk among disulfidptosis-related lncRNAs in lung adenocarcinoma reveals a correlation with immune profile and clinical prognosis

Disulfidptosis refers to a specific programmed cell death process characterized by the accumulation of disulfides. It has recently been reported in several cancers. However, the impact of disulfidptosis-related long non-coding RNAs (lncRNAs) on malignant tumors has remained largely unknown. In the present work, we screened prognostic disulfidptosis-related lncRNAs and studied their effects on lung adenocarcinoma. Relevant clinical data of lung adenocarcinoma cases were retrieved from The Cancer Genome Atlas (TCGA) database. RNA sequencing was used to identify differentially expressed disulfidptosis-related lncRNAs within lung adenocarcinoma. In addition, prognostic disulfidptosis-related lncRNAs were obtained through univariate Cox regression analysis. LASSO-COX was used to construct new disulfidptosis-related lncRNA signatures. Different statistical approaches were used to validate the practicability and accuracy of the disulfidptosis-related lncRNAs signatures. Furthermore, several bioinformatic approaches were used to study relevant heterogeneities in biological processes and pathways of diverse risk groups. Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was conducted to analyze the expression of disulfidptosis-related lncRNAs. Finally, seven disulfidptosis-related lncRNA signatures were identified in lung adenocarcinoma cells. The prognosis prediction model constructed efficiently predicted patient survival. Subgroup analysis revealed significant differences in immune cell proportion, including T follicular helper cells and M0 macrophages. In addition, in vitro experimental results demonstrated significant differences in disulfidptosis-related lncRNAs. Altogether, the six disulfidptosis-related lncRNA signatures could serve as a potential prognostic biomarker for lung adenocarcinoma. Furthermore, these can be used as a prediction model in individualized immunotherapy for lung adenocarcinoma.

The molecular basis of the anticancer effect of statins

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

Understanding P-Rex regulation: structural breakthroughs and emerging perspectives

Rho GTPases are a family of highly conserved G proteins that regulate numerous cellular processes, including cytoskeleton organisation, migration, and proliferation. The 20 canonical Rho GTPases are regulated by ∼85 guanine nucleotide exchange factors (GEFs), with the largest family being the 71 Diffuse B-cell Lymphoma (Dbl) GEFs. Dbl GEFs promote GTPase activity through the highly conserved Dbl homology domain. The specificity of GEF activity, and consequently GTPase activity, lies in the regulation and structures of the GEFs themselves. Dbl GEFs contain various accessory domains that regulate GEF activity by controlling subcellular localisation, protein interactions, and often autoinhibition. This review focuses on the two phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3)-dependent Rac exchangers (P-Rex), particularly the structural basis of P-Rex1 autoinhibition and synergistic activation. First, we discuss structures that highlight the conservation of P-Rex catalytic and phosphoinositide binding activities. We then explore recent breakthroughs in uncovering the structural basis for P-Rex1 autoinhibition and detail the proposed minimal two-step model of how PI(3,4,5)P3 and Gβγ synergistically activate P-Rex1 at the membrane. Additionally, we discuss the further layers of P-Rex regulation provided by phosphorylation and P-Rex2-PTEN coinhibitory complex formation, although these mechanisms remain incompletely understood. Finally, we leverage the available data to infer how cancer-associated mutations in P-Rex2 destabilise autoinhibition and evade PTEN coinhibitory complex formation, leading to increased P-Rex2 GEF activity and driving cancer progression and metastasis.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Unveiling the unique role of TSPAN7 across tumors: a pan-cancer study incorporating retrospective clinical research and bioinformatic analysis

BACKGROUND

TSPAN7 is an important factor in tumor progression. However, the precise function of TSPAN7 and its role in pan-cancer are not clear.

METHODS

Based on Xinhua cohort incorporating 370 patients with kidney neoplasm, we conducted differential expression analysis by immunohistochemistry between tumor and normal tissues, and explored correlations of TSPAN7 with patients' survival. Subsequently, we conducted a pan-cancer study, and successively employed differential expression analysis, competing endogenous RNA (ceRNA) analysis, protein-protein interaction (PPI) analysis, correlation analysis of TSPAN7 with clinical characteristics, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. Last but not least, gene set enrichment analysis was applied to identify enriched pathways of TSPAN7.

RESULTS

In Xinhua cohort, TSPAN7 expression was significantly up-regulated (P-value = 0.0019) in tumor tissues of kidney neoplasm patients. High TSPAN7 expression was associated with decreases in overall survival (OS) (P-value = 0.009) and progression-free survival (P-value = 0.009), and it was further revealed as an independent risk factor for OS (P-value = 0.0326, HR = 5.66, 95%CI = 1.155-27.8). In pan-cancer analysis, TSPAN7 expression was down-regulated in most tumors, and it was associated with patients' survival, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. The ceRNA network and PPI network of TSPAN7 were also constructed. Last but not least, the top five enriched pathways of TSPAN7 in various tumors were identified.

CONCLUSION

TSPAN7 served as a promising biomarker of various tumors, especially kidney neoplasms, and it was closely associated with tumor purity, tumor genomics, tumor immunology, and drug sensitivity in pan-cancer level.

Radiomic-Based Prediction of Lesion-Specific Systemic Treatment Response in Metastatic Disease

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 4.5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.70 for the most precise model (FDR = 0.05). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

Building a translational cancer dependency map for The Cancer Genome Atlas

Cancer dependency maps have accelerated the discovery of tumor vulnerabilities that can be exploited as drug targets when translatable to patients. The Cancer Genome Atlas (TCGA) is a compendium of 'maps' detailing the genetic, epigenetic and molecular changes that occur during the pathogenesis of cancer, yet it lacks a dependency map to translate gene essentiality in patient tumors. Here, we used machine learning to build translational dependency maps for patient tumors, which identified tumor vulnerabilities that predict drug responses and disease outcomes. A similar approach was used to map gene tolerability in healthy tissues to prioritize tumor vulnerabilities with the best therapeutic windows. A subset of patient-translatable synthetic lethalities were experimentally tested, including PAPSS1/PAPSS12 and CNOT7/CNOT78, which were validated in vitro and in vivo. Notably, PAPSS1 synthetic lethality was driven by collateral deletion of PAPSS2 with PTEN and was correlated with patient survival. Finally, the translational dependency map is provided as a web-based application for exploring tumor vulnerabilities.

Evaluating Immune Checkpoint Blockade in Metastatic Castration-Resistant Prostate Cancers with Deleterious CDK12 Alterations in the Phase 2 IMPACT Trial

PURPOSE

CDK12 inactivation in metastatic castration-resistant prostate cancer (mCRPC) may predict immunotherapy responses. This phase 2 trial evaluated the efficacy of immune checkpoint inhibitor (ICI) therapy in patients with CDK12-altered mCRPC.

PATIENTS AND METHODS

Eligible patients had mCRPC with deleterious CDK12 alterations and any prior therapies except ICI. Cohort A received ipilimumab (1 mg/kg) with nivolumab (3 mg/kg) every 3 weeks for up to four cycles, followed by nivolumab 480 mg every 4 weeks. Cohort C received nivolumab alone 480 mg every 4 weeks. Patients with CDK12-altered nonprostate tumors were enrolled in cohort B and not reported. The primary endpoint was a 50% reduction in PSA (PSA50). Key secondary endpoints included PSA progression-free survival, overall survival, objective response rate, and safety.

RESULTS

PSA was evaluable in 23 patients in cohort A and 14 in cohort C. Median lines of prior therapy were two in cohorts A and C, including any prior novel hormonal agent (74% and 79%) and chemotherapy (57% and 36%). The PSA50 rate was 9% [95% confidence interval (CI), 1%-28%] in cohort A with two responders; neither had microsatellite instability or a tumor mutational burden >10 mutations/megabase. No PSA50 responses occurred in cohort C. Median PSA progression-free survival was 7.0 months (95% CI, 3.6-11.4) in cohort A and 4.5 months (95% CI, 3.4-13.8) in cohort C. Median overall survival was 9.0 months (95% CI, 6.2-12.3) in cohort A and 13.8 months (95% CI, 3.6-not reached) in cohort C.

CONCLUSIONS

There was minimal activity with ICI therapy in patients with CDK12-altered mCRPC.

MYC and p53 alterations cooperate through VEGF signaling to repress cytotoxic T cell and immunotherapy responses in prostate cancer

Patients with castration-resistant prostate cancer (CRPC) are generally unresponsive to tumor targeted and immunotherapies. Whether genetic alterations acquired during the evolution of CRPC impact immune and immunotherapy responses is largely unknown. Using our innovative electroporation-based mouse models, we generated distinct genetic subtypes of CRPC found in patients and uncovered unique immune microenvironments. Specifically, mouse and human prostate tumors with MYC amplification and p53 disruption had weak cytotoxic lymphocyte infiltration and an overall dismal prognosis. MYC and p53 cooperated to induce tumor intrinsic secretion of VEGF, which by signaling through VEGFR2 expressed on CD8+ T cells, could directly inhibit T cell activity. Targeting VEGF-VEGFR2 signaling in vivo led to CD8+ T cell-mediated tumor and metastasis growth suppression and significantly increased overall survival in MYC and p53 altered CPRC. VEGFR2 blockade also led to induction of PD-L1, and in combination with PD-L1 immune checkpoint blockade produced anti-tumor efficacy in multiple preclinical CRPC mouse models. Thus, our results identify a genetic mechanism of immune suppression through VEGF signaling in prostate cancer that can be targeted to reactivate immune and immunotherapy responses in an aggressive subtype of CRPC.

Significance

Though immune checkpoint blockade (ICB) therapies can achieve curative responses in many treatment-refractory cancers, they have limited efficacy in CRPC. Here we identify a genetic mechanism by which VEGF contributes to T cell suppression, and demonstrate that VEGFR2 blockade can potentiate the effects of PD-L1 ICB to immunologically treat CRPC.

Genomic and computational-aided integrative drug repositioning strategy for EGFR and ROS1 mutated NSCLC

Non-small cell lung cancer (NSCLC) has been marked as the major cause of death in lung cancer patients. Due to tumor heterogeneity, mutation burden, and emerging resistance against the available therapies in NSCLC, it has been posing potential challenges in the therapy development. Hence, identification of cancer-driving mutations and their effective inhibition have been advocated as a potential approach in NSCLC treatment. Thereof, this study aims to employ the genomic and computational-aided integrative drug repositioning strategy to identify the potential mutations in the selected molecular targets and repurpose FDA-approved drugs against them. Accordingly, molecular targets and their mutations, i.e., EGFR (V843L, L858R, L861Q, and P1019L) and ROS1 (G1969E, F2046Y, Y2092C, and V2144I), were identified based on TCGA dataset analysis. Following, virtual screening and redocking analysis, Elbasvir, Ledipasvir, and Lomitapide drugs for EGFR mutants (>-10.8 kcal/mol) while Indinavir, Ledipasvir, Lomitapide, Monteleukast, and Isavuconazonium for ROS1 mutants (>-8.8 kcal/mol) were found as putative inhibitors. Furthermore, classical molecular dynamics simulation and endpoint binding energy calculation support the considerable stability of the selected docked complexes aided by substantial hydrogen bonding and hydrophobic interactions in comparison to the respective control complexes. Conclusively, the repositioned FDA-approved drugs might be beneficial alone or in synergy to overcome acquired resistance to EGFR and ROS1-positive lung cancers.

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

PIKfyve controls dendritic cell function and tumor immunity

The modern armamentarium for cancer treatment includes immunotherapy and targeted therapy, such as protein kinase inhibitors. However, the mechanisms that allow cancer-targeting drugs to effectively mobilize dendritic cells (DCs) and affect immunotherapy are poorly understood. Here, we report that among shared gene targets of clinically relevant protein kinase inhibitors, high PIKFYVE expression was least predictive of complete response in patients who received immune checkpoint blockade (ICB). In immune cells, high PIKFYVE expression in DCs was associated with worse response to ICB. Genetic and pharmacological studies demonstrated that PIKfyve ablation enhanced DC function via selectively altering the alternate/non-canonical NF-κB pathway. Both loss of Pikfyve in DCs and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively controls DCs, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

Liver metastases across cancer types sharing tumor environment immunotolerance can impede immune response therapy and immune monitoring

BACKGROUND

Hepatic immune tolerance might contribute to the development of therapeutic resistance to immunotherapy. However, addressing this issue is challenging since the efficacy of immunotherapy in the context of liver metastasis (LM) remains poorly studied. Here, we aimed to establish an LM common immune feature (LMCIF) score to quantify the characteristics of LM immunotolerance across cancer types for assisting clinical disease management.

METHODS

Large-scale clinical data were collected to identify the prognosis of LM. Multi-omics datasets of metastatic cancers with LM special immune-related pathways (LMSIPs) from the Molecular Signatures Database (MSigDB)were used to obtain an LMCIF cluster. Based on differential expression genes (DEGs), a novel LMCIF score for the LMCIF cluster was constructed. In addition, multi-omics, and immunohistochemistry (IHC) data from the public and in-house cohorts were used to explore the features of LM, and LMCIF score.

RESULTS

Patients with LM had a worse prognosis and significantly lower infiltration of immune cells than patients with metastasis to other organs when analyzed with combined clinical and RNA sequencing data. After extracting the LMCIF cluster from 373 samples by utilizing 29 LMSIPs and validating them in a microarray cohort, an LMCIF score was established to confirm the role of the immunosuppressive environment as a contributor to the poor prognosis of LM across cancer types. Moreover, this LMCIF score could be used to predict the immune response of cancer patients undergoing immunotherapy. Finally, we identified that the majority of the 31 LMCIF genes exhibited a negative correlation with TME cells in LM patients, one of them, KRT19, which possessed the strongest positive correlation with LMCIF score, was confirmed to have an immunosuppressive effect through IHC analysis.

CONCLUSIONS

Our results suggest that LM across cancer types share similar immunological profiles that induce immunotolerance and escape from immune monitoring. The novel LMCIF score represents a common liver metastasis immune cluster for predicting immunotherapy response, the results of which might benefit clinical disease management.

PIKfyve, expressed by CD11c-positive cells, controls tumor immunity

Cancer treatment continues to shift from utilizing traditional therapies to targeted ones, such as protein kinase inhibitors and immunotherapy. Mobilizing dendritic cells (DC) and other myeloid cells with antigen presenting and cancer cell killing capacities is an attractive but not fully exploited approach. Here, we show that PIKFYVE is a shared gene target of clinically relevant protein kinase inhibitors and high expression of this gene in DCs is associated with poor patient response to immune checkpoint blockade (ICB) therapy. Genetic and pharmacological studies demonstrate that PIKfyve ablation enhances the function of CD11c+ cells (predominantly dendritic cells) via selectively altering the non-canonical NF-κB pathway. Both loss of Pikfyve in CD11c+ cells and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively regulates the function of CD11c+ cells, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.