Integrative clinical genomics of metastatic cancer

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.

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.

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.

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.

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).

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.

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.

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.

DNA damage targeted therapy for advanced breast cancer

Breast cancer (BC) is the most prevalent malignancy affecting women worldwide, including Portugal. While the majority of BC cases are sporadic, hereditary forms account for 5-10% of cases. The most common inherited mutations associated with BC are germline mutations in the BReast CAncer (BRCA) 1/2 gene (gBRCA1/2). They are found in approximately 5-6% of BC patients and are inherited in an autosomal dominant manner, primarily affecting younger women. Pathogenic variants within BRCA1/2 genes elevate the risk of both breast and ovarian cancers and give rise to distinct clinical phenotypes. BRCA proteins play a key role in maintaining genome integrity by facilitating the repair of double-strand breaks through the homologous recombination (HR) pathway. Therefore, any mutation that impairs the function of BRCA proteins can result in the accumulation of DNA damage, genomic instability, and potentially contribute to cancer development and progression. Testing for gBRCA1/2 status is relevant for treatment planning, as it can provide insights into the likely response to therapy involving platinum-based chemotherapy and poly[adenosine diphosphate (ADP)-ribose] polymerase inhibitors (PARPi). The aim of this review was to investigate the impact of HR deficiency in BC, focusing on BRCA mutations and their impact on the modulation of responses to platinum and PARPi therapy, and to share the experience of Unidade Local de Saúde Santa Maria in the management of metastatic BC patients with DNA damage targeted therapy, including those with the Portuguese c.156_157insAlu BRCA2 founder mutation.

Structural and pharmacological insights into cordycepin for neoplasms and metabolic disorders

Cytotoxic adenosine analogues were among the earliest chemotherapeutic agents utilised in cancer treatment. Cordycepin, a natural derivative of adenosine discovered in the fungus Ophiocordyceps sinensis, directly inhibits tumours not only by impeding biosynthesis, inducing apoptosis or autophagy, regulating the cell cycle, and curtailing tumour invasion and metastasis but also modulates the immune response within the tumour microenvironment. Furthermore, extensive research highlights cordycepin's significant therapeutic potential in alleviating hyperlipidaemia and regulating glucose metabolism. This review comprehensively analyses the structure-activity relationship of cordycepin and its analogues, outlines its pharmacokinetic properties, and strategies to enhance its bioavailability. Delving into the molecular biology, it explores the pharmacological mechanisms of cordycepin in tumour suppression and metabolic disorder treatment, thereby underscoring its immense potential in drug development within these domains and laying the groundwork for innovative treatment strategies.

Rare pathogenic structural variants show potential to enhance prostate cancer germline testing for African men

Prostate cancer (PCa) is highly heritable, with men of African ancestry at greatest risk and associated lethality. Lack of representation in genomic data means germline testing guidelines exclude for African men. Established that structural variations (SVs) are major contributors to human disease and prostate tumourigenesis, their role is under-appreciated in familial and therapeutic testing. Utilising a clinico-methodologically matched African (n = 113) versus European (n = 57) deep-sequenced PCa resource, we interrogated 42,966 high-quality germline SVs using a best-fit pathogenicity prediction workflow. We identified 15 potentially pathogenic SVs representing 12.4% African and 7.0% European patients, of which 72% and 86% met germline testing standard-of-care recommendations, respectively. Notable African-specific loss-of-function gene candidates include DNA damage repair MLH1 and BARD1 and tumour suppressors FOXP1, WASF1 and RB1. Representing only a fraction of the vast African diaspora, this study raises considerations with respect to the contribution of kilo-to-mega-base rare variants to PCa pathogenicity and African associated disparity.

Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

ASXLs binding to the PHD2/3 fingers of MLL4 provides a mechanism for the recruitment of BAP1 to active enhancers

The human methyltransferase and transcriptional coactivator MLL4 and its paralog MLL3 are frequently mutated in cancer. MLL4 and MLL3 monomethylate histone H3K4 and contain a set of uncharacterized PHD fingers. Here, we report a novel function of the PHD2 and PHD3 (PHD2/3) fingers of MLL4 and MLL3 that bind to ASXL2, a component of the Polycomb repressive H2AK119 deubiquitinase (PR-DUB) complex. The structure of MLL4 PHD2/3 in complex with the MLL-binding helix (MBH) of ASXL2 and mutational analyses reveal the molecular mechanism which is conserved in homologous ASXL1 and ASXL3. The native interaction of the Trithorax MLL3/4 complexes with the PR-DUB complex in vivo depends solely on MBH of ASXL1/2, coupling the two histone modifying activities. ChIP-seq analysis in embryonic stem cells demonstrates that MBH of ASXL1/2 is required for the deubiquitinase BAP1 recruitment to MLL4-bound active enhancers. Our findings suggest an ASXL1/2-dependent functional link between the MLL3/4 and PR-DUB complexes.

Patient-Derived Tumor Xenograft Study with CDK4/6 Inhibitor Plus AKT Inhibitor for the Management of Metastatic Castration-Resistant Prostate Cancer

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive malignancy with poor outcomes. To investigate novel therapeutic strategies, we characterized three new metastatic prostate cancer patient derived-tumor xenograft (PDTX) models and developed 3D spheroids from each to investigate molecular targeted therapy combinations including CDK4/6 inhibitors (CDK4/6i) with AKT inhibitors (ATKi). Metastatic prostate cancer tissue was collected and three PDTX models were established and characterized using whole-exome sequencing. PDTX 3D spheroids were developed from these three PDTXs to show resistance patterns and test novel molecular-targeted therapies. CDK4/6i's were combined with AKTi's to assess synergistic antitumor response to prove our hypothesis that blockade of AKT overcomes drug resistance to CDK4/6i. This combination was evaluated in PDTX three-dimensional (3D) spheroids and in vivo experiments with responses measured by tumor volumes, PSA, and Ga-68 PSMA-11 PET-CT imaging. We demonstrated CDK4/6i's with AKTi's possess synergistic antitumor activity in three mCRPC PDTX models. These models have multiple unique pathogenic and deleterious genomic alterations with resistance to single-agent CDK4/6i's. Despite this, combination therapy with AKTi's was able to overcome resistance mechanisms. The IHC and Western blot analysis confirmed on target effects, whereas tumor volume, serum PSA ELISA, and radionuclide imaging demonstrated response to therapy with statistically significant SUV differences seen with Ga-68 PSMA-11 PET-CT. These preclinical data demonstrating antitumor synergy by overcoming single-agent CDK 4/6i as well as AKTi drug resistance provide the rational for a clinical trial combining a CDK4/6i with an AKTi in patients with mCRPC whose tumor expresses wild-type retinoblastoma 1.

DUX4 is a common driver of immune evasion and immunotherapy failure in metastatic cancers

Cancer immune evasion contributes to checkpoint immunotherapy failure in many patients with metastatic cancers. The embryonic transcription factor DUX4 was recently characterized as a suppressor of interferon-γ signaling and antigen presentation that is aberrantly expressed in a small subset of primary tumors. Here, we report that DUX4 expression is a common feature of metastatic tumors, with ~10-50% of advanced bladder, breast, kidney, prostate, and skin cancers expressing DUX4. DUX4 expression is significantly associated with immune cell exclusion and decreased objective response to PD-L1 blockade in a large cohort of urothelial carcinoma patients. DUX4 expression is a significant predictor of survival even after accounting for tumor mutational burden and other molecular and clinical features in this cohort, with DUX4 expression associated with a median reduction in survival of over 1 year. Our data motivate future attempts to develop DUX4 as a biomarker and therapeutic target for checkpoint immunotherapy resistance.

Liver tropism of ER mutant breast cancer is characterized by unique molecular changes and immune infiltration

PURPOSE

Hotspot estrogen receptor alpha (ER/ESR1) mutations are recognized as the driver for both endocrine resistance and metastasis in advanced ER-positive (ER+) breast cancer, but their contributions to metastatic organ tropism remain insufficiently understood. In this study, we aim to comprehensively profile the organotropic metastatic pattern for ESR1 mutant breast cancer.

METHODS

The organ-specific metastatic pattern of ESR1 mutant breast cancer was delineated using multi-omics data from multiple publicly available cohorts of ER+ metastatic breast cancer patients. Gene mutation/copy number variation (CNV) and differential gene expression analyses were performed to identify the genomic and transcriptomic alterations uniquely associated with ESR1 mutant liver metastasis. Upstream regulator, downstream pathway, and immune infiltration analysis were conducted for subsequent mechanistic investigations.

RESULTS

ESR1 mutation-driven liver tropism was revealed by significant differences, encompassing a higher prevalence of liver metastasis in patients with ESR1 mutant breast cancer and an enrichment of mutations in liver metastatic samples. The significant enrichment of AGO2 copy number amplifications (CNAs) and multiple gene expression changes were revealed uniquely in ESR1 mutant liver metastasis. We also unveiled alterations in downstream signaling pathways and immune infiltration, particularly an enrichment of neutrophils, suggesting potential therapeutic vulnerabilities.

CONCLUSION

Our data provide a comprehensive characterization of the behaviors and mechanisms of ESR1 mutant liver metastasis, paving the way for the development of personalized therapy to target liver metastasis for patients with ESR1 mutant breast cancer.

Comprehensive proteogenomic characterization of rare kidney tumors

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Distinct molecular profiles drive multifaceted characteristics of colorectal cancer metastatic seeds

Metastasis of primary tumors remains a challenge for early diagnosis and prevention. The cellular properties and molecular drivers of metastatically competent clones within primary tumors remain unclear. Here, we generated 10-16 single cell-derived lines from each of three colorectal cancer (CRC) tumors to identify and characterize metastatic seeds. We found that intrinsic factors conferred clones with distinct metastatic potential and cellular communication capabilities, determining organ-specific metastasis. Poorly differentiated or highly metastatic clones, rather than drug-resistant clones, exhibited poor clinical prognostic impact. Personalized genetic alterations, instead of mutation burden, determined the occurrence of metastatic potential during clonal evolution. Additionally, we developed a gene signature for capturing metastatic potential of primary CRC tumors and demonstrated a strategy for identifying metastatic drivers using isogenic clones with distinct metastatic potential in primary tumors. This study provides insight into the origin and mechanisms of metastasis and will help develop potential anti-metastatic therapeutic targets for CRC patients.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Breaking paradigms: Long non-coding RNAs forming gene fusions with potential implications in cancer

Long non-coding RNAs (lncRNAs) are non-coding RNAs longer than 200 nucleotides with dynamic regulatory functions. They interact with a wide range of molecules such as DNA, RNA, and proteins to modulate diverse cellular functions through several mechanisms and, if deregulated, they can lead to cancer development and progression. Recently, it has been described that lncRNAs are susceptible to form gene fusions with mRNAs or other lncRNAs, breaking the paradigm of gene fusions consisting mainly of protein-coding genes. However, their biological significance in the tumor phenotype is still uncertain. Therefore, their recent identification opens a new line of research to study their biological role in tumorigenesis, and their potential as biomarkers with clinical relevance or as therapeutic targets. The present study aimed to review the lncRNA fusions identified so far and to know which of them have been associated with a potential function. We address the current challenges to deepen their study as well as the reasons why they represent a future therapeutic window in cancer.

[Molecular pathological analysis through the ages]

BACKGROUND

Molecular pathological examinations of tumor samples encompass a wide range of diagnostic analyses. Especially in recent years, numerous new biomarkers have come to the forefront-the analysis of which is crucial for therapy decisions.

OBJECTIVES

Within the field of molecular pathology, the demands of next generation sequencing (NGS)-based requirements have experienced massive growth in recent years. To meet this demand, methods are constantly being adapted and further developed. The following sections aim to illuminate how this trend arises and which analyses are gaining importance.

METHODS

The article provides an overview of the essential nucleic acid-based analysis techniques in the field of massive parallel sequencing. Terms such as DNA- and RNA-based techniques, as well as the associated analysis methods, are described, particularly with regard to their use in routine molecular pathological diagnostics.

RESULTS

The breadth of genomic sequencing has been steadily growing in recent years, particularly due to the increasing relevance of personalized medicine, along with the rising approvals of targeted therapeutics. This necessitates, among other things, the analysis of new biomarkers. The diagnostics as part of interdisciplinary molecular tumor boards (MTB) are now based on large gene panels (> 1 megabase). Furthermore, through the "Modellvorhaben Genomsequenzierung" § 64e, whole exome or whole genome sequencing has been made available for oncological patients. Given these developments, it is evident that future analyses will require the integration of additional omics fields, such as whole transcriptome analysis, epigenomics, and proteomics.

CONCLUSION

The challenges of personalized medicine along with the necessity of simultaneously assessing numerous new biomarkers require the implementation and execution of new techniques in molecular pathology whose complexity is steadily increasing.

KRAS Allelic Variants in Biliary Tract Cancers

Importance

Biliary tract cancers (BTCs) contain several actionable molecular alterations, including FGFR2, IDH1, ERBB2 (formerly HER2), and KRAS. KRAS allelic variants are found in 20% to 30% of BTCs, and multiple KRAS inhibitors are currently under clinical investigation.

Objectives

To describe the genomic landscape, co-sequence variations, immunophenotype, genomic ancestry, and survival outcomes of KRAS-mutated BTCs and to calculate the median overall survival (mOS) for the most common allelic variants.

Design, Setting, and Participants

This retrospective, multicenter, pooled cohort study obtained clinical and next-generation sequencing data from multiple databases between January 1, 2017, and December 31, 2022. These databases included Princess Margaret Cancer Centre, MD Anderson Cancer Center, Foundation Medicine, American Association for Cancer Research Project GENIE, and cBioPortal for Cancer Genomics. The cohort comprised patients with BTCs who underwent genomic testing.

Main Outcome and Measure

The main outcome was mOS, defined as date of diagnosis to date of death, which was measured in months.

Results

A total of 7457 patients (n = 3773 males [50.6%]; mean [SD] age, 63 [5] years) with BTCs and genomic testing were included. Of these patients, 5813 had clinical outcome data available, in whom 1000 KRAS-mutated BTCs were identified. KRAS allelic variants were highly prevalent in perihilar cholangiocarcinoma (28.6%) and extrahepatic cholangiocarcinoma (36.1%). Thirty-six KRAS allelic variants were identified, and the prevalence rates in descending order were G12D (41%), G12V (23%), and Q61H (8%). The variant G12D had the highest mOS of 25.1 (95% CI, 22.0-33.0) months compared with 22.8 (95% CI, 19.6-31.4) months for Q61H and 17.8 (95% CI, 16.3-23.1) months for G12V variants. The majority of KRAS-mutated BTCs (98.9%) were not microsatellite instability-high and had low tumor mutational burden (ranging from a median [IQR] of 1.2 (1.2-2.5) to a mean [SD] of 3.3 [1.3]). Immune profiling through RNA sequencing of KRAS and NRAS-mutated samples showed a pattern toward a more immune-inflamed microenvironment with higher M1 macrophage activation (0.16 vs 0.12; P = .047) and interferon-γ expression compared with wild-type tumors. The G12D variant remained the most common KRAS allelic variant in all patient ancestries. Patients with admixed American ancestry had the highest proportion of G12D variant (45.0%).

Conclusions and Relevance

This cohort study found that KRAS allelic variants were relatively common and may be potentially actionable genomic alterations in patients with BTCs, especially perihilar cholangiocarcinoma and extrahepatic cholangiocarcinoma. The findings add to the growing data on genomic and immune landscapes of KRAS allelic variants in BTCs and are potentially of value to the planning of specific therapies for this heterogeneous patient group.

Androgen receptor splice variants drive castration-resistant prostate cancer metastasis by activating distinct transcriptional programs

One critical mechanism through which prostate cancer (PCa) adapts to treatments targeting androgen receptor (AR) signaling is the emergence of ligand-binding domain-truncated and constitutively active AR splice variants, particularly AR-V7. While AR-V7 has been intensively studied, its ability to activate distinct biological functions compared with the full-length AR (AR-FL), and its role in regulating the metastatic progression of castration-resistant PCa (CRPC), remain unclear. Our study found that, under castrated conditions, AR-V7 strongly induced osteoblastic bone lesions, a response not observed with AR-FL overexpression. Through combined ChIP-seq, ATAC-seq, and RNA-seq analyses, we demonstrated that AR-V7 uniquely accesses the androgen-responsive elements in compact chromatin regions, activating a distinct transcription program. This program was highly enriched for genes involved in epithelial-mesenchymal transition and metastasis. Notably, we discovered that SOX9, a critical metastasis driver gene, was a direct target and downstream effector of AR-V7. Its protein expression was dramatically upregulated in AR-V7-induced bone lesions. Moreover, we found that Ser81 phosphorylation enhanced AR-V7's pro-metastasis function by selectively altering its specific transcription program. Blocking this phosphorylation with CDK9 inhibitors impaired the AR-V7-mediated metastasis program. Overall, our study has provided molecular insights into the role of AR splice variants in driving the metastatic progression of CRPC.

A Metastatic Cancer Expression Generator (MetGen): A Generative Contrastive Learning Framework for Metastatic Cancer Generation

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

Metastatic organotropism: a brief overview

Organotropism has been known since 1889, yet this vital component of metastasis has predominantly stayed elusive. This mini-review gives an overview of the current understanding of the underlying mechanisms of organotropism and metastases development by focusing on the formation of the pre-metastatic niche, immune defenses against metastases, and genomic alterations associated with organotropism. The particular case of brain metastases is also addressed, as well as the impact of organotropism in cancer therapy. The limited comprehension of the factors behind organotropism underscores the necessity for efficient strategies and treatments to manage metastases.