Multi-omics characterization of autophagy-related molecular features for therapeutic targeting of autophagy

Combination of betulinic acid and EGFR-TKIs exerts synergistic anti-tumor effects against wild-type EGFR NSCLC by inducing autophagy-related cell death via EGFR signaling pathway

BACKGROUND

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of lung cancer patients with mutated EGFR. However, the efficacy of EGFR-TKIs in wild-type EGFR tumors has been shown to be marginal. Methods that can sensitize EGFR-TKIs to EGFR wild-type NSCLC remain rare. Hence, we determined whether combination treatment can maximize the therapeutic efficacy of EGFR-TKIs.

METHODS

We established a focused drug screening system to investigate candidates for overcoming the intrinsic resistance of wild-type EGFR NSCLC to EGFR-TKIs. Molecular docking assays and western blotting were used to identify the binding mode and blocking effect of the candidate compounds. Proliferation assays, analyses of drug interactions, colony formation assays, flow cytometry and nude mice xenograft models were used to determine the effects and investigate the molecular mechanism of the combination treatment.

RESULTS

Betulinic acid (BA) is effective at targeting EGFR and synergizes with EGFR-TKIs (gefitinib and osimertinib) preferentially against wild-type EGFR. BA showed inhibitory activity due to its interaction with the ATP-binding pocket of EGFR and dramatically enhanced the suppressive effects of EGFR-TKIs by blocking EGFR and modulating the EGFR-ATK-mTOR axis. Mechanistic studies revealed that the combination strategy activated EGFR-induced autophagic cell death and that the EGFR-AKT-mTOR signaling pathway was essential for completing autophagy and cell cycle arrest. Activation of the mTOR pathway or blockade of autophagy by specific chemical agents markedly attenuated the effect of cell cycle arrest. In vivo administration of the combination treatment caused marked tumor regression in the A549 xenografts.

CONCLUSIONS

BA is a potential wild-type EGFR inhibitor that plays a critical role in sensitizing EGFR-TKI activity. BA combined with an EGFR-TKI effectively suppressed the proliferation and survival of intrinsically resistant lung cancer cells via the inhibition of EGFR as well as the induction of autophagy-related cell death, indicating that BA combined with an EGFR-TKI may be a potential therapeutic strategy for overcoming the primary resistance of wild-type EGFR-positive lung cancers.

Multiomics approach towards characterization of tumor cell plasticity and its significance in precision and personalized medicine

Cellular plasticity refers to the ability of cells to change their identity or behavior, which can be advantageous in some cases (e.g., tissue regeneration) but detrimental in others (e.g., cancer metastasis). With a better understanding of cellular plasticity, the complexity of cancer cells, their heterogeneity, and their role in metastasis is being unraveled. The plasticity of the cells could also prove as a nemesis to their characterization. In this review, we have attempted to highlight the possibilities and benefits of using multiomics approach in characterizing the plastic nature of cancer cells. There is a need to integrate fragmented evidence at different levels of cellular organization (DNA, RNA, protein, metabolite, epigenetics, etc.) to facilitate the characterization of different forms of plasticity and cell types. We have discussed the role of cellular plasticity in generating intra-tumor heterogeneity. Different omics level evidence is being provided to highlight the variety of molecular determinants discovered using different techniques. Attempts have been made to integrate some of this information to provide a quantitative assessment and scoring of the plastic nature of the cells. However, there is a huge gap in our understanding of mechanisms that lead to the observed heterogeneity. Understanding of these mechanism(s) is necessary for finding targets for early detection and effective therapeutic interventions in metastasis. Targeting cellular plasticity is akin to neutralizing a moving target. Along with the advancements in precision and personalized medicine, these efforts may translate into better clinical outcomes for cancer patients, especially in metastatic stages.

When autophagy meets placenta development and pregnancy complications

Autophagy is a common biological phenomenon in eukaryotes that has evolved and reshaped to maintain cellular homeostasis. Under the pressure of starvation, hypoxia, and immune damage, autophagy provides energy and nutrients to cells, which benefits cell survival. In mammals, autophagy is an early embryonic nutrient supply system involved in early embryonic development, implantation, and pregnancy maintenance. Recent studies have found that autophagy imbalance in placental tissue plays a key role in the occurrence and development of pregnancy complications, such as gestational hypertension, gestational obesity, premature birth, miscarriage, and intrauterine growth restriction. This mini-review summarizes the molecular mechanism of autophagy regulation, the autophagy pathways, and related factors involved in placental tissue and comprehensively describes the role of autophagy in pregnancy complications.

Unveiling autophagy complexity in leukemia: The molecular landscape and possible interactions with apoptosis and ferroptosis

Autophagy is a self-digestion multistep process in which causes the homeostasis through degradation of macromolecules and damaged organelles. The autophagy-mediated tumor progression regulation has been a critical point in recent years, revealing the function of this process in reduction or acceleration of carcinogenesis. Leukemia is a haematological malignancy in which abnormal expansion of hematopoietic cells occurs. The current and conventional therapies from chemotherapy to cell transplantation have failed to appropriately treat the leukemia patients. Among the mechanisms dysregulated in leukemia, autophagy is a prominent one in which can regulate the hallmarks of this tumor. The protective autophagy inhibits apoptosis and ferroptosis in leukemia, while toxic autophagy accelerates cell death. The proliferation and invasion of tumor cells are tightly regulated by the autophagy. The direction of regulation depends on the function of autophagy that is protective or lethal. The protective autophagy accelerates chemoresistance and radio-resistsance. The non-coding RNAs, histone transferases and other pathways such as PI3K/Akt/mTOR are among the regulators of autophagy in leukemia progression. The pharmacological intervention for the inhibition or induction of autophagy by the compounds including sesamine, tanshinone IIA and other synthetic compounds can chance progression of leukemia.

T proliferating cells derived autophagy signature associated with prognosis and immunotherapy resistance in a pan-cancer analysis

Despite autophagy modulating tumor immunity in the tumor microenvironment (TME), the immunotherapeutic efficacy and potential mechanism of autophagy signature was not explicit. We manually curated an autophagy gene set and defined a pan-cancer autophagy signature by comparing malignant tissues and normal tissues in The Cancer Genome Atlas (TCGA) cohort. The pan-cancer autophagy signature was derived from T proliferating cells as demonstrated in multiple single-cell RNA sequencing (scRNA-seq) datasets. The pan-cancer autophagy signature could influence the cell-cell interactions in the TME and predict the responsiveness of immune checkpoint inhibitors (ICIs) in the metastatic renal cell carcinoma, non-small cell lung cancer, bladder cancer, and melanoma cohorts. Metabolism inactivation accompanied with dysregulation of autophagy was investigated with transcriptomic and proteomic data. The immunotherapeutic predictive role and mechanism regulation of the autophagy signature was validated in an in-house cohort. Our study provides valuable insights into the mechanisms of ICI resistance.

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.

Nanomedicine-induced programmed cell death enhances tumor immunotherapy

BACKGROUND

There has been widespread concern about the high cancer mortality rate and the shortcomings of conventional cancer treatments. Immunotherapy is a novel oncology therapy with high efficiency and low side effects, which is a revolutionary direction for clinical oncology treatment. However, its clinical effectiveness is uneven. Based on the redefinition and reclassification of programmed cell death (PCD) (divided into necroptosis, ferroptosis, pyroptosis, and autophagy), the role of nanomedicine-induced PCD in cancer therapy has also received significant attention. Clinical and preclinical studies have begun to combine PCD with immunotherapy.

AIM OF REVIEW

In this article, we present recent research in tumor immunotherapy, provide an overview of how nanomedicine-induced PCD is involved in tumor therapy, and review how nanomedicine-induced PCD can improve the limitations of immunotherapy to enhance tumor immunotherapy. The future development of nanomedicine-mediated PCD tumor therapy and tumor immunotherapy is also proposed Key scientific concepts of overview Nanomedicine-induced PCD is a prospective method of tumor immunotherapy. Nanomedicines increase tumor site penetration and targeting ability, and nanomedicine-mediated PCD activation can stimulate powerful anti-tumor immune effects, which has a good contribution to immunotherapy of tumors.

Autophagy induction sensitizes cancer cells to anti-cancer drugs

Resistance to anti-cancer therapy is a major challenge for cancer treatment. Many studies revealed that macroautophagy/autophagy inhibition can overcome autophagy-mediated therapy resistance, but these efforts have not yet led to the success of clinical applications. In a recent paper, we established a 37-gene autophagy signature to estimate the autophagy status of approximately 10,000 tumor samples across 33 cancer types from The Cancer Genome Atlas, and muti-omics characterization reveals that autophagy induction may also sensitize cancer cells to anti-cancer drugs. These findings provide a comprehensive resource of molecular alterations associated with autophagy and highlight the potential to utilize drug sensitivity induced by autophagy to overcome the resistance of cancer therapy.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Multi-omics characterization of synthetic lethality-related molecular features: implications for SL-based therapeutic target screening

Synthetic lethality (SL) represents the co-occurrence of two or more non-lethal disordered genes that could lead to cell death. SL-based anticancer therapeutics could specifically kill the cancer cells carrying the targeted mutated gene while leaving normal cells alive. Recent large-scale computational and experimental screenings provide rich resources of SL information while lacking systematic research on molecular features of SL genes. Combined with comprehensive multi-omics data analysis and experimental validation of one SL gene pair, Guo et al. portrayed a systematic layout of cancer-specific SL interactions that could improve understanding of carcinogenesis and potentially assist the subsequent screening of anticancer therapeutic targets.

Comprehensive analysis of autophagy-related clusters and individual risk model for immunotherapy response prediction in gastric cancer

Introduction

Autophagy can be triggered by oxidative stress and is a double-edged sword involved in the progression of multiple malignancies. However, the precise roles of autophagy on immune response in gastric cancer (GC) remain clarified.

Methods

We endeavor to explore the novel autophagy-related clusters and develop a multi-gene signature for predicting the prognosis and the response to immunotherapy in GC. A total of 1505 patients from eight GC cohorts were categorized into two subtypes using consensus clustering. We compare the differences between clusters by the multi-omics approach. Cox and LASSO regression models were used to construct the prognostic signature.

Results

Two distinct clusters were identified. Compared with cluster 2, the patients in cluster 1 have favorable survival outcomes and lower scores for epithelial-mesenchymal transition (EMT). The two subtypes are further characterized by high heterogeneity concerning immune cell infiltration, somatic mutation pattern, and pathway activity by gene set enrichment analysis (GSEA). We obtained 21 autophagy-related differential expression genes (DEGs), in which PTK6 amplification and BCL2/CDKN2A deletion were highly prevalent. The four-gene (PEA15, HSPB8, BNIP3, and GABARAPL1) risk signature was further constructed with good predictive performance and validated in 3 independent datasets including our local Tianjin cohort. The risk score was proved to be independent prognostic factor. A prognostic nomogram showed robust validity of GC survival. The risk score was significantly associated with immune cell infiltration status, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint molecules. Furthermore, the model was efficient for predicting the response to tumor-targeted agent and immunotherapy and verified by the IMvigor210 cohort. This model is also capable of discriminating between low and high-risk patients receiving chemotherapy.

Conclusion

Altogether, our exploratory research on the landscape of autophagy-related patterns may shed light on individualized therapies and prognosis in GC.