Integrative multi-omics and drug-response characterization of patient-derived prostate cancer primary cells

Pharmacological induction of MHC-I expression in tumor cells revitalizes T cell antitumor immunity

Antigen presentation by major histocompatibility complex class I (MHC-I) is crucial for T cell-mediated killing, and aberrant surface MHC-I expression is tightly associated with immune evasion. To address MHC-I downregulation, we conducted a high-throughput flow cytometry screen, identifying bleomycin (BLM) as a potent inducer of cell surface MHC-I expression. BLM-induced MHC-I augmentation rendered tumor cells more susceptible to T cells in coculture assays and enhanced antitumor responses in an adoptive cellular transfer mouse model. Mechanistically, BLM remodeled the tumor immune microenvironment, inducing MHC-I expression in a manner dependent on ataxia-telangiectasia mutated/ataxia telangiectasia and Rad3-related-NF-κB. Furthermore, BLM improved T cell-dependent immunotherapeutic approaches, including bispecific antibody therapy, immune checkpoint therapy, and autologous tumor-infiltrating lymphocyte therapy. Importantly, low-dose BLM treatment in mouse models amplified the antitumor effect of immunotherapy without detectable pulmonary toxicity. In summary, our findings repurpose BLM as a potential inducer of MHC-I, enhancing its expression to improve the efficacy of T cell-based immunotherapy.

AGR2: The Covert Driver and New Dawn of Hepatobiliary and Pancreatic Cancer Treatment

The anterior gradient protein 2 (AGR2) plays a crucial role in facilitating the formation of protein disulfide bonds within the endoplasmic reticulum (ER). Research suggests that AGR2 can function as an oncogene, with its heightened expression linked to the advancement of hepatobiliary and pancreatic cancers through invasion and metastasis. Notably, AGR2 not only serves as a pro-oncogenic agent but also as a downstream targeting protein, indirectly fostering cancer progression. This comprehensive review delves into the established functions and expression patterns of AGR2, emphasizing its pivotal role in cancer progression, particularly in hepatobiliary and pancreatic malignancies. Furthermore, AGR2 emerges as a potential cancer prognostic marker and a promising target for immunotherapy, offering novel avenues for the treatment of hepatobiliary and pancreatic cancers and enhancing patient outcomes.

Multi Omics Applications in Biological Systems

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Patient-Derived Conditionally Reprogrammed Cells in Prostate Cancer Research

Prostate cancer (PCa) remains a leading cause of mortality among American men, with metastatic and recurrent disease posing significant therapeutic challenges due to a limited comprehension of the underlying biological processes governing disease initiation, dormancy, and progression. The conventional use of PCa cell lines has proven inadequate in elucidating the intricate molecular mechanisms driving PCa carcinogenesis, hindering the development of effective treatments. To address this gap, patient-derived primary cell cultures have been developed and play a pivotal role in unraveling the pathophysiological intricacies unique to PCa in each individual, offering valuable insights for translational research. This review explores the applications of the conditional reprogramming (CR) cell culture approach, showcasing its capability to rapidly and effectively cultivate patient-derived normal and tumor cells. The CR strategy facilitates the acquisition of stem cell properties by primary cells, precisely recapitulating the human pathophysiology of PCa. This nuanced understanding enables the identification of novel therapeutics. Specifically, our discussion encompasses the utility of CR cells in elucidating PCa initiation and progression, unraveling the molecular pathogenesis of metastatic PCa, addressing health disparities, and advancing personalized medicine. Coupled with the tumor organoid approach and patient-derived xenografts (PDXs), CR cells present a promising avenue for comprehending cancer biology, exploring new treatment modalities, and advancing precision medicine in the context of PCa. These approaches have been used for two NCI initiatives (PDMR: patient-derived model repositories; HCMI: human cancer models initiatives).

AGR2-mediated unconventional secretion of 14-3-3ε and α-actinin-4, responsive to ER stress and autophagy, drives chemotaxis in canine mammary tumor cells

BACKGROUND

Canine mammary tumors (CMTs) in intact female dogs provide a natural model for investigating metastatic human cancers. Our prior research identified elevated expression of Anterior Gradient 2 (AGR2), a protein disulfide isomerase (PDI) primarily found in the endoplasmic reticulum (ER), in CMT tissues, highly associated with CMT progression. We further demonstrated that increased AGR2 expression actively influences the extracellular microenvironment, promoting chemotaxis in CMT cells. Unraveling the underlying mechanisms is crucial for assessing the potential of therapeutically targeting AGR2 as a strategy to inhibit a pro-metastatic microenvironment and impede tumor metastasis.

METHODS

To identify the AGR2-modulated secretome, we employed proteomics analysis of the conditioned media (CM) from two CMT cell lines ectopically expressing AGR2, compared with corresponding vector-expressing controls. AGR2-regulated release of 14-3-3ε (gene: YWHAE) and α-actinin 4 (gene: ACTN4) was validated through ectopic expression, knockdown, and knockout of the AGR2 gene in CMT cells. Extracellular vesicles derived from CMT cells were isolated using either differential ultracentrifugation or size exclusion chromatography. The roles of 14-3-3ε and α-actinin 4 in the chemotaxis driven by the AGR2-modulated CM were investigated through gene knockdown, antibody-mediated interference, and recombinant protein supplement. Furthermore, the clinical relevance of the release of 14-3-3ε and α-actinin 4 was assessed using CMT tissue-immersed saline and sera from CMT-afflicted dogs.

RESULTS

Proteomics analysis of the AGR2-modulated secretome revealed increased abundance in 14-3-3ε and α-actinin 4. Ectopic expression of AGR2 significantly increased the release of 14-3-3ε and α-actinin 4 in the CM. Conversely, knockdown or knockout of AGR2 expression remarkably reduced their release. Silencing 14-3-3ε or α-actinin 4 expression diminished the chemotaxis driven by AGR2-modulated CM. Furthermore, AGR2 controls the release of 14-3-3ε and α-actinin 4 primarily via non-vesicular routes, responding to the endoplasmic reticulum (ER) stress and autophagy activation. Knockout of AGR2 resulted in increased α-actinin 4 accumulation and impaired 14-3-3ε translocation in autophagosomes. Depletion of extracellular 14-3-3ε or α-actinin 4 reduced the chemotaxis driven by AGR2-modulated CM, whereas supplement with recombinant 14-3-3ε in the CM enhanced the CM-driven chemotaxis. Notably, elevated levels of 14-3-3ε or α-actinin 4 were observed in CMT tissue-immersed saline compared with paired non-tumor samples and in the sera of CMT dogs compared with healthy dogs.

CONCLUSION

This study elucidates AGR2's pivotal role in orchestrating unconventional secretion of 14-3-3ε and α-actinin 4 from CMT cells, thereby contributing to paracrine-mediated chemotaxis. The insight into the intricate interplay between AGR2-involved ER stress, autophagy, and unconventional secretion provides a foundation for refining strategies aimed at impeding metastasis in both canine mammary tumors and potentially human cancers.

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Proteomics Identifies LUC7L3 as a Prognostic Biomarker for Hepatocellular Carcinoma

Alternative splicing has been shown to participate in tumor progression, including hepatocellular carcinoma. The poor prognosis of patients with HCC calls for molecular classification and biomarker identification to facilitate precision medicine. We performed ssGSEA analysis to quantify the pathway activity of RNA splicing in three HCC cohorts. Kaplan-Meier and Cox methods were used for survival analysis. GO and GSEA were performed to analyze pathway enrichment. We confirmed that RNA splicing is significantly correlated with prognosis, and identified an alternative splicing-associated protein LUC7L3 as a potential HCC prognostic biomarker. Further bioinformatics analysis revealed that high LUC7L3 expression indicated a more progressive HCC subtype and worse clinical features. Cell proliferation-related pathways were enriched in HCC patients with high LUC7L3 expression. Consistently, we proved that LUC7L3 knockdown could significantly inhibit cell proliferation and suppress the activation of associated signaling pathways in vitro. In this research, the relevance between RNA splicing and HCC patient prognosis was outlined. Our newly identified biomarker LUC7L3 could provide stratification for patient survival and recurrence risk, facilitating early medical intervention before recurrence or disease progression.

Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis

Oncolytic viruses (OVs) are the frontier therapy for refractory cancers, especially in integration with immunomodulation strategies. In cancer immunovirotherapy, the many available "omics" and systems biology technologies generate at a fast pace a challenging huge amount of data, where apparently clashing information mirrors the complexity of individual clinical situations and OV used. In this review, we present and discuss how currently big data analysis, on one hand and, on the other, simulation, modeling, and computational technologies, provide invaluable support to interpret and integrate "omic" information and drive novel synthetic biology and personalized OV engineering approaches for effective immunovirotherapy. Altogether, these tools, possibly aided in the future by artificial intelligence as well, will allow for the blending of the information into OV recombinants able to achieve tumor clearance in a patient-tailored way. Various endeavors to the envisioned "synthesis" of turning OVs into personalized theranostic agents are presented.