Validation of Selected Head and Neck Cancer Prognostic Markers from the Pathology Atlas in an Oral Tongue Cancer Cohort

Exploring the Enigma: The Role of the Epithelial Protein Lost in Neoplasm in Normal Physiology and Cancer Pathogenesis

The cytoskeleton plays a pivotal role in maintaining the epithelial phenotype and is vital to several hallmark processes of cancer. Over the past decades, researchers have identified the epithelial protein lost in neoplasm (EPLIN, also known as LIMA1) as a key regulator of cytoskeletal dynamics, cytoskeletal organization, motility, as well as cell growth and metabolism. Dysregulation of EPLIN is implicated in various aspects of cancer progression, such as tumor growth, invasion, metastasis, and therapeutic resistance. Its altered expression levels or activity can disrupt cytoskeletal dynamics, leading to aberrant cell motility and invasiveness characteristic of malignant cells. Moreover, the involvement of EPLIN in cell growth and metabolism underscores its significance in orchestrating key processes essential for cancer cell survival and proliferation. This review provides a comprehensive exploration of the intricate roles of EPLIN across diverse cellular processes in both normal physiology and cancer pathogenesis. Additionally, this review discusses the possibility of EPLIN as a potential target for anticancer therapy in future studies.

Spatial Transcriptomic and Metabolomic Landscapes of Oral Submucous Fibrosis-Derived Oral Squamous Cell Carcinoma and its Tumor Microenvironment

In South and Southeast Asia, the habit of chewing betel nuts is prevalent, which leads to oral submucous fibrosis (OSF). OSF is a well-established precancerous lesion, and a portion of OSF cases eventually progress to oral squamous cell carcinoma (OSCC). However, the specific molecular mechanisms underlying the malignant transformation of OSCC from OSF are poorly understood. In this study, the leading-edge techniques of Spatial Transcriptomics (ST) and Spatial Metabolomics (SM) are integrated to obtain spatial location information of cancer cells, fibroblasts, and immune cells, as well as the transcriptomic and metabolomic landscapes in OSF-derived OSCC tissues. This work reveals for the first time that some OSF-derived OSCC cells undergo partial epithelial-mesenchymal transition (pEMT) within the in situ carcinoma (ISC) region, eventually acquiring fibroblast-like phenotypes and participating in collagen deposition. Complex interactions among epithelial cells, fibroblasts, and immune cells in the tumor microenvironment are demonstrated. Most importantly, significant metabolic reprogramming in OSF-derived OSCC, including abnormal polyamine metabolism, potentially playing a pivotal role in promoting tumorigenesis and immune evasion is discovered. The ST and SM data in this study shed new light on deciphering the mechanisms of OSF-derived OSCC. The work also offers invaluable clues for the prevention and treatment of OSCC.

A novel oxidative stress-related gene signature as an indicator of prognosis and immunotherapy responses in HNSCC

PURPOSE

To identify molecular subtypes of oxidative stress-related genes in head and neck squamous cell carcinoma (HNSCC) and to construct a scoring model of oxidative stress-related genes.

METHODS

R language based scRNA-seq and bulk RNA-seq analyses were used to identify molecular isoforms of oxidative stress-related genes in HNSCC. An oxidative stress-related gene scoring (OSRS) model was constructed, which were verified through online data and immunohistochemical staining of clinical samples.

RESULTS

Using TCGA-HNSCC datasets, nine predictive genes for overall patient survival, rarely reported in previous similar studies, were screened. AREG and CES1 were identified as prognostic risk factors. CSTA, FDCSP, JCHAIN, IFFO2, PGLYRP4, SPOCK2 and SPINK6 were identified as prognostic factors. Collectively, all genes formed a prognostic risk signature model for oxidative stress in HNSCC, which were validated in GSE41613, GSE103322 and PRJEB23709 datasets. Immunohistochemical staining of SPINK6 in nasopharyngeal cancer samples validated the gene panel. Subsequent analysis indicated that subgroups of the oxidative stress prognostic signature played important roles during cellular communication, the immune microenvironment, the differential activation of transcription factors, oxidative stress and immunotherapeutic responses.

CONCLUSIONS

The risk model might predict HNSCC prognosis and immunotherapeutic responses.

Characterization of LIMA1 and its emerging roles and potential therapeutic prospects in cancers

Actin is the most abundant and highly conserved cytoskeletal protein present in all eukaryotic cells. Remodeling of the actin cytoskeleton is controlled by a variety of actin-binding proteins that are extensively involved in biological processes such as cell motility and maintenance of cell shape. LIM domain and actin-binding protein 1 (LIMA1), as an important actin cytoskeletal regulator, was initially thought to be a tumor suppressor frequently downregulated in epithelial tumors. Importantly, the deficiency of LIMA1 may be responsible for dysregulated cytoskeletal dynamics, altered cell motility and disrupted cell-cell adhesion, which promote tumor proliferation, invasion and migration. As research progresses, the roles of LIMA1 extend from cytoskeletal dynamics and cell motility to cell division, gene regulation, apical extrusion, angiogenesis, cellular metabolism and lipid metabolism. However, the expression of LIMA1 in malignant tumors and its mechanism of action have not yet been elucidated, and many problems and challenges remain to be addressed. Therefore, this review systematically describes the structure and biological functions of LIMA1 and explores its expression and regulatory mechanism in malignant tumors, and further discusses its clinical value and therapeutic prospects.

Dalpiciclib partially abrogates ER signaling activation induced by pyrotinib in HER2+HR+ breast cancer

Recent evidences from clinical trials (NCT04486911) revealed that the combination of pyrotinib, letrozole, and dalpiciclib exerted optimistic therapeutic effect in treating HER2⁺HR⁺ breast cancer; however, the underlying molecular mechanism remained elusive. Through the drug sensitivity test, the drug combination efficacy of pyrotinib, tamoxifen, and dalpiciclib to BT474 cells was tested. The underlying molecular mechanisms were investigated using immunofluorescence, Western blot analysis, immunohistochemical staining, and cell cycle analysis. Potential risk factor that may indicate the responsiveness to drug treatment in HER2⁺/HR⁺ breast cancer was identified using RNA-sequence and evaluated using immunohistochemical staining and in vivo drug susceptibility test. We found that pyrotinib combined with dalpiciclib exerted better cytotoxic efficacy than pyrotinib combined with tamoxifen in BT474 cells. Degradation of HER2 could enhance ER nuclear transportation, activating ER signaling pathway in BT474 cells, whereas dalpiciclib could partially abrogate this process. This may be the underlying mechanism by which combination of pyrotinib, tamoxifen, and dalpiciclib exerted best cytotoxic effect. Furthermore, CALML5 was revealed to be a risk factor in the treatment of HER2⁺/HR⁺ breast cancer and the usage of dalpiciclib might overcome the drug resistance to pyrotinib + tamoxifen due to CALML5 expression. Our study provided evidence that the usage of dalpiciclib in the treatment of HER2⁺/HR⁺ breast cancer could partially abrogate the estrogen signaling pathway activation caused by anti-HER2 therapy and revealed that CALML5 could serve as a risk factor in the treatment of HER2⁺/HR⁺ breast cancer.

Cell type ontologies of the Human Cell Atlas

Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body while at the same time raising the need to formalize this new knowledge. Here, we discuss current efforts to harmonize and integrate different sources of annotations of cell types and states into a reference cell ontology. We illustrate with examples how a unified ontology can consolidate and advance our understanding of cell types across scientific communities and biological domains.

Epithelial protein lost in neoplasm (EPLIN) and prostate cancer: lessons learned from the ARCaP model

Confucius said, "Good tools are prerequisite to the successful execution of a job". Among his many groundbreaking achievements, Dr. Leland W. K. Chung established several widely used prostate cancer (PCa) cell lines, including C4-2, C4-2B, and ARCaP. These cellular models have been pivotal tools to enhance our understanding of the biology of PCa progression and assist in the discovery of new strategies to treat metastatic, castration-resistant PCa. Recent studies in the ARCaP PCa progression model uncovered epithelial protein lost in neoplasm (EPLIN), an actin-binding protein with an indispensable role in the maintenance of epithelial structures, as a negative regulator of epithelial-mesenchymal transition. Clinical evidence further supports the potential role of EPLIN in controlling metastasis in PCa and other solid tumors. In this article, we review the current understanding of the biology of EPLIN and the ARCaP model in the discovery of new agents for the prevention and treatment of PCa metastasis.

A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.