Immunometabolic coevolution defines unique microenvironmental niches in ccRCC

UnitedMet harnesses RNA-metabolite covariation to impute metabolite levels in clinical samples

Comprehensively studying metabolism requires the measurement of metabolite levels. However, in contrast to the broad availability of gene expression data, metabolites are rarely measured in large molecularly-defined cohorts of tissue samples. To address this basic barrier to metabolic discovery, we propose a Bayesian framework ("UnitedMet") which leverages the empirical strength of RNA-metabolite covariation to impute otherwise unmeasured metabolite levels from widely available transcriptomic data. We demonstrate that UnitedMet is equally capable of imputing whole pool sizes as well as the outcomes of isotope tracing experiments. We apply UnitedMet to investigate the metabolic impact of driver mutations in kidney cancer, identifying a novel association between BAP1 and a highly oxidative tumor phenotype. We similarly apply UnitedMet to determine that advanced kidney cancers upregulate oxidative phosphorylation relative to early-stage disease, that oxidative metabolism in kidney cancer is associated with inferior outcomes to combination therapy, and that kidney cancer metastases themselves demonstrate elevated oxidative phosphorylation relative to primary tumors. UnitedMet therefore enables the assessment of metabolic phenotypes in contexts where metabolite measurements were not taken or are otherwise infeasible, opening new avenues for the generation and evaluation of metabolite-centered hypotheses. UnitedMet is open source and publicly available ( https://github.com/reznik-lab/UnitedMet ).

iModMix: Integrative Module Analysis for Multi-omics Data

The integration of metabolomics with other omics ("multi-omics") offers complementary insights into disease biology. However, this integration remains challenging due to the fragmented landscape of current methodologies, which often require programming experience or bioinformatics expertise. Moreover, existing approaches are limited in their ability to accommodate unidentified metabolites, resulting in the exclusion of a significant portion of data from untargeted metabolomics experiments. Here, we introduce iModMix, a novel approach that uses a graphical lasso to construct network modules for integration and analysis of multi-omics data. iModMix uses a horizontal integration strategy, allowing metabolomics data to be analyzed alongside proteomics or transcriptomics to explore complex molecular associations within biological systems. Importantly, it can incorporate both annotated and unidentified metabolites, addressing a key limitation of existing methodologies. iModMix is available as a user-friendly R Shiny application that requires no programming experience (https://imodmix.moffitt.org), and it includes example data from several publicly available multi-omic studies for exploration. An R package is available for advanced users (https://github.com/biodatalab/iModMix).

Availability and implementation

Shiny application: https://imodmix.moffitt.org. The R package and source code: https://github.com/biodatalab/iModMix.

STAC3 as a poor prognostic biomarker in renal clear cell carcinoma: relationship with immune infiltration

Calcium ions (Ca2+) are crucial in tumorigenesis and progression, with their elevated levels indicating a negative prognosis in Kidney Renal Clear Cell Carcinoma (KIRC). The influence of genes regulating calcium ions on the survival outcomes of KIRC patients and their interaction with the tumor's immune microenvironment is yet to be fully understood. This study analyzed gene expression data from KIRC tumor and adjacent non-tumor tissues using the TCGA-KIRC dataset to pinpoint genes that are differentially expressed in KIRC. Intersection of these genes with those regulating calcium ions highlighted specific calcium ion-regulating genes that exhibit differential expression in KIRC. Subsequently, prognostic risk models were developed using univariate Cox and LASSO-Cox regression analyses to verify their diagnostic precision. Additionally, the study investigated the correlation between tumor immunity and KIRC patient outcomes, assessing the contribution of STAC3 genes to tumor immunity. Further exploration entailed SSGASE, single-cell analysis, pseudotime analysis and both in vivo and in vitro experiments to evaluate STAC3's role in tumor immunity and progression. Notably, STAC3 was significantly overexpressed in tumor specimens and positively correlated with the degree of malignancy of KIRC, affecting patients' prognosis. Elevated STAC3 expression correlated with enhanced immune infiltration in KIRC tumors. Furthermore, silencing STAC3 curtailed KIRC cell proliferation, migration, invasion, and stemness properties. Experimental models in mice confirmed that STAC3 knockdown led to a reduction in tumor growth. Elevated STAC3 expression is intricately linked with immune infiltration in KIRC tumors, as well as with the aggressive biological behaviors of tumor cells, including their proliferation, migration, and invasion. Targeting STAC3 presents a promising strategy to augment the efficacy of current therapeutic approaches and to better the survival outcomes of patients with KIRC.

B cell lymphoma 6 promotes hepatocellular carcinoma progression by inhibiting tumor infiltrating CD4+T cell cytotoxicity through ESM1

Immunotherapy exhibited potential effects for advanced hepatocellular carcinoma, unfortunately, the clinical benefits are often countered by cancer adaptive immune suppressive response. Uncovering the mechanism how cancer cells evade immune surveillance would help to develop new immunotherapy approaches and combination therapy. In this article, by analyzing the transcriptional factors which modulate the differentially expressed genes between T cell infiltration high group and low group, we identified oncoprotein B cell lymphoma 6 (BCL6) suppresses the infiltration and activation of tumor infiltrating T lymphocytes, thus correlated with poorer clinical outcome. By using antibody deletion experiment, we further demonstrated that CD4+T cells but not CD8+T cells are the main lymphocyte population suppressed by Bcl6 to promote HCC development. Mechanistically, BCL6 decreases cancer cell expression of pro-inflammatory cytokines and T lymphocyte chemokines such as IL6, IL1F6, and CCL5. Moreover, BCL6 upregulates Endothelial cell-specific molecule 1 (ESM1) to inhibit T lymphocyte recruitment and activation possibly through ICAM-1/LFA-1 signaling pathway. Our findings uncovered an unappreciated paracrine mechanism how cancer cell-derived BCL6 assists cancer cell immune evasion, and highlighted the role of CD4+T cells in HCC immune surveillance.

Metabolic engineering for optimized CAR-T cell therapy

The broad effectiveness of T cell-based therapy for treating solid tumour cancers remains limited. This is partly due to the growing appreciation that immune cells must inhabit and traverse a metabolically demanding tumour environment. Accordingly, recent efforts have centred on using genome-editing technologies to augment T cell-mediated cytotoxicity by manipulating specific metabolic genes. However, solid tumours exhibit numerous characteristics restricting immune cell-mediated cytotoxicity, implying a need for metabolic engineering at the pathway level rather than single gene targets. This emerging concept has yet to be put into clinical practice as many questions concerning the complex interplay between metabolic networks and T cell function remain unsolved. This Perspective will highlight key foundational studies that examine the relevant metabolic pathways required for effective T cell cytotoxicity and persistence in the human tumour microenvironment, feasible strategies for metabolic engineering to increase the efficiency of chimeric antigen receptor T cell-based approaches, and the challenges lying ahead for clinical implementation.

Long-Term Survival of Patients with Stage T1N0M1 Renal Cell Carcinoma

Metastatic renal cell carcinoma (RCC) is among the most lethal urological malignancies. However, small, localized RCCs (≤7 cm, stage T1) have an excellent prognosis. There is a rare patient subgroup diagnosed with synchronous distant metastasis (T1N0M1), of which very little is known in terms of survival outcomes and underlying disease biology. Herein, we examined the long-term survival of 27 patients with clear cell RCC (ccRCC) stage T1N0M1 in comparison to 18 patients without metastases (T1N0M0). Tumor tissue was stained by immunohistochemistry for CD8+ tumor infiltrating lymphocytes (TILs). As expected, patients with stage T1N0M1 showed a significantly worse median cancer specific survival (CSS; 2.8 years) than patients with stage T1N0M0 (17.7 years; HR 0.077; 95% CI, 0.022-0.262). However, eight patients (29.6%) with ccRCC stage T1N0M1 survived over five years, and three of those patients (11.1%) survived over a decade. Some of these patients benefitted from an intensified, multimodal treatment including metastasis-directed therapy. The number of CD8+ TILs was substantially higher in stage T1N0M1 ccRCCs than in stage T1N0M0 ccRCCs, suggesting a more aggressive tumor biology. In conclusion, long-term survival is possible in patients with ccRCC stage T1N0M1, with some patients benefitting from an intensified, multimodal treatment approach.

Molecular landmarks of tumor disulfidptosis across cancer types to promote disulfidptosis-target therapy

The mystery about the mechanistic basis of disulfidptosis has recently been unraveled and shows promise as an effective treatment modality for triggering cancer cell death. However, the limited understanding of the role of disulfidptosis in tumor progression and drug sensitivity has hindered the development of disulfidptosis-targeted therapy and combinations with other therapeutic strategies. Here, we established a disulfidptosis signature model to estimate tumor disulfidptosis status in approximately 10,000 tumor samples across 33 cancer types and revealed its prognostic value. Then, we characterized disulfidptosis-associated molecular features and identified various types of molecular alterations that correlate with both drug-resistant and drug-sensitive responses to anti-tumor drugs. We further showed the vast heterogeneity in disulfidptosis status among 760 cancer cell lines across 25 cancer types. We experimentally validated that disulfidptosis score-high cell lines are more susceptible to glucose starvation-induced disulfidptosis compared to their counterparts with low scores. Finally, we investigated the impact of disulfidptosis status on drug response and revealed that disulfidptosis induction may enhance sensitivity to anti-cancer drugs, but in some cases, it could also lead to drug resistance in cultured cells. Overall, our multi-omics analysis firstly elucidates a comprehensive profile of disulfidptosis-related molecular alterations, prognosis, and potential therapeutic therapies at a pan-cancer level. These findings may uncover opportunities to utilize multiple drug sensitivities induced by disulfidptosis, thereby offering practical implications for clinical cancer therapy.

The immunometabolic ecosystem in cancer

Our increased understanding of how key metabolic pathways are activated and regulated in malignant cells has identified metabolic vulnerabilities of cancers. Translating this insight to the clinics, however, has proved challenging. Roadblocks limiting efficacy of drugs targeting cancer metabolism may lie in the nature of the metabolic ecosystem of tumors. The exchange of metabolites and growth factors between cancer cells and nonmalignant tumor-resident cells is essential for tumor growth and evolution, as well as the development of an immunosuppressive microenvironment. In this Review, we will examine the metabolic interplay between tumor-resident cells and how targeted inhibition of specific metabolic enzymes in malignant cells could elicit pro-tumorigenic effects in non-transformed tumor-resident cells and inhibit the function of tumor-specific T cells. To improve the efficacy of metabolism-targeted anticancer strategies, a holistic approach that considers the effect of metabolic inhibitors on major tumor-resident cell populations is needed.

Acid-sensing ion channel 1a modulation of apoptosis in acidosis-related diseases: implications for therapeutic intervention

Acid-sensing ion channel 1a (ASIC1a), a prominent member of the acid-sensing ion channel (ASIC) superfamily activated by extracellular protons, is ubiquitously expressed throughout the human body, including the nervous system and peripheral tissues. Excessive accumulation of Ca2+ ions via ASIC1a activation may occur in the acidified microenvironment of blood or local tissues. ASIC1a-mediated Ca2+‑induced apoptosis has been implicated in numerous pathologies, including neurological disorders, cancer, and rheumatoid arthritis. This review summarizes the role of ASIC1a in the modulation of apoptosis via various signaling pathways across different disease states to provide insights for future studies on the underlying mechanisms and development of therapeutic strategies.