Cancer-associated fibroblasts impact the clinical outcome and treatment response in colorectal cancer via immune system modulation: a comprehensive genome-wide analysis

Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.

Tumor-associated mesenchymal stromal cells modulate macrophage phagocytosis in stromal-rich colorectal cancer via PD-1 signaling

CMS4 colorectal cancer (CRC), based on the consensus molecular subtype (CMS), stratifies patients with the poorest disease-free survival rates. It is characterized by a strong mesenchymal stromal cell (MSC) signature, wound healing-like inflammation and therapy resistance. We utilized 2D and 3D in vitro, in vivo, and ex vivo models to assess the impact of inflammation and stromal cells on immunosuppression in CMS4 CRC. RNA sequencing data from untreated stage II/III CRC patients showed enriched TNF-α signatures in CMS1 and CMS4 tumors. Secretome from TNF-α treated cancer cells induced an immunomodulatory and chemotactic phenotype in MSC and cancer-associated fibroblasts (CAFs). Macrophages in CRC tumours migrate and preferentially localise in stromal compartment. Inflammatory CRC secretome enhances expression of PD-L1 and CD47 on both human and murine stromal cells. We demonstrate that TNF-α-induced inflammation in CRC suppresses macrophage phagocytosis via stromal cells. We show that stromal cell-mediated suppression of macrophage phagocytosis is mediated in part through PD-1 signaling. These data suggest that re-stratification of CRC by CMS may reveal patient subsets with microsatellite stable tumors, particularly CMS4-like tumors, that may respond to immunotherapies.

Targeting the devil: Strategies against cancer-associated fibroblasts in colorectal cancer

Cancer-associated fibroblasts (CAFs), as significant constituents of the tumor microenvironment (TME), play a pivotal role in the progression of cancers, including colorectal cancer (CRC). In this comprehensive review, we presented the origins and activation mechanisms of CAFs in CRC, elaborating on how CAFs drive tumor progression through their interactions with CRC cells, immune cells, vascular endothelial cells, and the extracellular matrix within the TME. We systematically outline the intricate web of interactions among CAFs, tumor cells, and other TME components, and based on this complex interplay, we summarize various therapeutic strategies designed to target CAFs in CRC. It is also essential to recognize that CAFs represent a highly heterogeneous group, encompassing various subtypes such as myofibroblastic CAF (myCAF), inflammatory CAF (iCAF), antigen-presenting CAF (apCAF), vessel-associated CAF (vCAF). Herein, we provide a summary of studies investigating the heterogeneity of CAFs in CRC and the characteristic expression patterns of each subtype. While the majority of CAFs contribute to the exacerbation of CRC malignancy, recent findings have revealed specific subtypes that exert inhibitory effects on CRC progression. Nevertheless, the comprehensive landscape of CAF heterogeneity still awaits exploration. We also highlight pivotal unanswered questions that need to be addressed before CAFs can be recognized as feasible targets for cancer treatment. In conclusion, the aim of our review is to elucidate the significance and challenges of advancing in-depth research on CAFs, while outlining the pathway to uncover the complex roles of CAFs in CRC and underscore their significant potential as therapeutic targets.

An Analysis Regarding the Association Between DAZ Interacting Zinc Finger Protein 1 (DZIP1) and Colorectal Cancer (CRC)

Colorectal cancer (CRC) is the third most common malignant disease worldwide, and its incidence is increasing, but the molecular mechanisms of this disease are highly heterogeneous and still far from being fully understood. Increasing evidence suggests that fibrosis mediated by abnormal activation of fibroblasts based in the microenvironment is associated with a poor prognosis. However, the function and pathogenic mechanisms of fibroblasts in CRC remain unclear. Here, combining scrna-seq and clinical specimen data, DAZ Interacting Protein 1 (DZIP1) was found to be expressed on fibroblasts and cancer cells and positively correlated with stromal deposition. Importantly, pseudotime-series analysis showed that DZIP1 levels were up-regulated in malignant transformation of fibroblasts and experimentally confirmed that DZIP1 modulates activation of fibroblasts and promotes epithelial-mesenchymal transition (EMT) in tumor cells. Further studies showed that DZIP1 expressed by tumor cells also has a driving effect on EMT and contributes to the recruitment of more fibroblasts. A similar phenomenon was observed in xenografted nude mice. And it was confirmed in xenograft mice that downregulation of DZIP1 expression significantly delayed tumor formation and reduced tumor size in CRC cells. Taken together, our findings suggested that DZIP1 was a regulator of the CRC mesenchymal phenotype. The revelation of targeting DZIP1 provides a new avenue for CRC therapy.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Computational identification and clinical validation of a novel risk signature based on coagulation-related lncRNAs for predicting prognosis, immunotherapy response, and chemosensitivity in colorectal cancer patients

Background

Coagulation is critically involved in the tumor microenvironment, cancer progression, and prognosis assessment. Nevertheless, the roles of coagulation-related long noncoding RNAs (CRLs) in colorectal cancer (CRC) remain unclear. In this study, an integrated computational framework was constructed to develop a novel coagulation-related lncRNA signature (CRLncSig) to stratify the prognosis of CRC patients, predict response to immunotherapy and chemotherapy in CRC, and explore the potential molecular mechanism.

Methods

CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the substantial bulk or single-cell RNA transcriptomics from Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR (RT-qPCR) data from CRC cell lines and paired frozen tissues were used for validation. We performed unsupervised consensus clustering of CRLs to classify patients into distinct molecular subtypes. We then used stepwise regression to establish the CRLncSig risk model, which stratified patients into high- and low-risk groups. Subsequently, diversified bioinformatics algorithms were used to explore prognosis, biological pathway alteration, immune microenvironment, immunotherapy response, and drug sensitivity across patient subgroups. In addition, weighted gene coexpression network analysis was used to construct an lncRNA-miRNA-mRNA competitive endogenous network. Expression levels of CRLncSig, immune checkpoints, and immunosuppressors were determined using RT-qPCR.

Results

We identified two coagulation subclusters and constructed a risk score model using CRLncSig in CRC, where the patients in cluster 2 and the low-risk group had a better prognosis. The cluster and CRLncSig were confirmed as the independent risk factors, and a CRLncSig-based nomogram exhibited a robust prognostic performance. Notably, the cluster and CRLncSig were identified as the indicators of immune cell infiltration, immunoreactivity phenotype, and immunotherapy efficiency. In addition, we identified a new endogenous network of competing CRLs with microRNA/mRNA, which will provide a foundation for future mechanistic studies of CRLs in the malignant progression of CRC. Moreover, CRLncSig strongly correlated with drug susceptibility.

Conclusion

We developed a reliable CRLncSig to predict the prognosis, immune landscape, immunotherapy response, and drug sensitivity in patients with CRC, which might facilitate optimizing risk stratification, guiding the applications of immunotherapy, and individualized treatments for CRC.

Exosome nanovesicles as potential biomarkers and immune checkpoint signaling modulators in lung cancer microenvironment: recent advances and emerging concepts

Lung cancer remains the leading cause of cancer-related deaths globally, and the survival rate remains low despite advances in diagnosis and treatment. The progression of lung cancer is a multifaceted and dynamic phenomenon that encompasses interplays among cancerous cells and their microenvironment, which incorporates immune cells. Exosomes, which are small membrane-bound vesicles, are released by numerous cell types in normal and stressful situations to allow communication between cells. Tumor-derived exosomes (TEXs) possess diverse neo-antigens and cargoes such as proteins, RNA, and DNA and have a unique molecular makeup reflecting tumor genetic complexity. TEXs contain both immunosuppressive and immunostimulatory factors and may play a role in immunomodulation by influencing innate and adaptive immune components. Moreover, they transmit signals that contribute to the progression of lung cancer by promoting metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunosuppression. This makes them a valuable resource for investigating the immune environment of tumors, which could pave the way for the development of non-invasive biomarkers that could aid in the prognosis, diagnosis, and immunotherapy of lung cancer. While immune checkpoint inhibitor (ICI) immunotherapy has shown promising results in treating initial-stage cancers, most patients eventually develop adaptive resistance over time. Emerging evidence demonstrates that TEXs could serve as a prognostic biomarker for immunotherapeutic response and have a significant impact on both systemic immune suppression and tumor advancement. Therefore, understanding TEXs and their role in lung cancer tumorigenesis and their response to immunotherapies is an exciting research area and needs further investigation. This review highlights the role of TEXs as key contributors to the advancement of lung cancer and their clinical significance in lung immune-oncology, including their possible use as biomarkers for monitoring disease progression and prognosis, as well as emerging shreds of evidence regarding the possibility of using exosomes as targets to improve lung cancer therapy.

Cancer-on-chip: a 3D model for the study of the tumor microenvironment

The approval of anticancer therapeutic strategies is still slowed down by the lack of models able to faithfully reproduce in vivo cancer physiology. On one hand, the conventional in vitro models fail to recapitulate the organ and tissue structures, the fluid flows, and the mechanical stimuli characterizing the human body compartments. On the other hand, in vivo animal models cannot reproduce the typical human tumor microenvironment, essential to study cancer behavior and progression. This study reviews the cancer-on-chips as one of the most promising tools to model and investigate the tumor microenvironment and metastasis. We also described how cancer-on-chip devices have been developed and implemented to study the most common primary cancers and their metastatic sites. Pros and cons of this technology are then discussed highlighting the future challenges to close the gap between the pre-clinical and clinical studies and accelerate the approval of new anticancer therapies in humans.

YAP1 controls the N-cadherin-mediated tumor-stroma interaction in melanoma progression

Epithelial-to-mesenchymal transition (EMT) is crucial for melanoma cells to escape keratinocyte control, invade underlying dermal tissues, and metastasize to distant organs. The hallmark of EMT is the switch from epithelial cadherin (E-cadherin) to neural cadherin (N-cadherin), allowing melanoma cells to form a homotypic N-cadherin-mediated adhesion with stromal fibroblasts. However, how "cadherin switching" is initiated, maintained, and regulated in melanoma remains unknown. Here, we show that upon Yes-associated protein 1 (YAP1) ablation in cancer-associated fibroblasts (CAFs), the progression of a BRAF-mutant mouse melanoma was significantly suppressed in vivo, and overexpressing YAP1 in CAFs accelerated melanoma growth. CAFs require the YAP1 function to proliferate, migrate, remodel the cytoskeletal machinery and matrix, and promote cancer cell invasion. By RNA-Seq, N-cadherin was identified as a major downstream effector of YAP1 signaling in CAFs. YAP1 silencing led to N-cadherin downregulation in CAFs, which subsequently induced the downregulation of N-cadherin in neighboring melanoma cells. N-cadherin downregulation inhibited the PI3K-AKT signaling pathway in melanoma cells and suppressed melanoma growth in vivo, supporting the role of N-cadherin as an adhesive and signaling molecule in melanoma cells. This finding suggests that YAP1 depletion in CAFs induces the downregulation of p-AKT signaling in melanoma cells through the N-cadherin-mediated interaction between melanoma cells and CAFs. Importantly, our data underscore that CAFs can regulate N-cadherin-mediated interactions with melanoma cells. Thus, disentangling cadherin-mediated cell-cell interactions can potentially disrupt tumor-stroma interactions and reverse the tumor cell invasive phenotype.

Heterogeneity and function of cancer-associated fibroblasts in renal cell carcinoma

With the advancement of anticancer therapy, there is increasing interest in understanding the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) play a pivotal role in the TME and have been the focus of much research in recent years. CAFs play an active role in cancer progression through complex interactions with other cells in the TME, releasing regulatory factors, synthesizing and remodeling the extracellular matrix. However, research on the role of CAFs in renal cell carcinoma (RCC) is still in its nascent stages. Here, we describe the origins and subgroups of CAFs, the roles of CAFs in the development and progression of RCC, the impact of CAFs on RCC prognosis, and the potential of CAFs as treatment targets in RCC. By analyzing CAF subsets, biomarkers, and targeted therapies, we present the significance and contribution of CAFs in RCC research. Furthermore, we highlight the distinct contribution of CAFs in advanced RCC through horizontal comparison with other cancers. This paper provides a comprehensive perspective of recent and foundational studies on the role of CAFs in RCC and other types of cancers and new insights for further study of CAFs in RCC.

Identification of Spatial Proteomic Signatures of Colon Tumor Metastasis: A Digital Spatial Profiling Approach

Over 150,000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually >50,000 individuals are estimated to die of CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. CRC tumors are removed en bloc with surrounding vasculature and lymphatics. Examination of regional lymph nodes at the time of surgical resection is essential for prognostication. Developing alternative approaches to indirectly assess recurrence risk would have utility in cases where lymph node yield is incomplete or inadequate. Spatially dependent, immune cell-specific (eg, tumor-infiltrating lymphocytes), proteomic, and transcriptomic expression patterns inside and around the tumor-the tumor immune microenvironment-can predict nodal/distant metastasis and probe the coordinated immune response from the primary tumor site. The comprehensive characterization of tumor-infiltrating lymphocytes and other immune infiltrates is possible using highly multiplexed spatial omics technologies, such as the GeoMX Digital Spatial Profiler. In this study, machine learning and differential co-expression analyses helped identify biomarkers from Digital Spatial Profiler-assayed protein expression patterns inside, at the invasive margin, and away from the tumor, associated with extracellular matrix remodeling (eg, granzyme B and fibronectin), immune suppression (eg, forkhead box P3), exhaustion and cytotoxicity (eg, CD8), Programmed death ligand 1-expressing dendritic cells, and neutrophil proliferation, among other concomitant alterations. Further investigation of these biomarkers may reveal independent risk factors of CRC metastasis that can be formulated into low-cost, widely available assays.

Liquid biopsy approaches and immunotherapy in colorectal cancer for precision medicine: Are we there yet?

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths globally, with nearly half of patients detected in the advanced stages. This is due to the fact that symptoms associated with CRC often do not appear until the cancer has reached an advanced stage. This suggests that CRC is a cancer with a slow progression, making it curable and preventive if detected in its early stage. Therefore, there is an urgent clinical need to improve CRC early detection and personalize therapy for patients with this cancer. Recently, liquid biopsy as a non-invasive or nominally invasive approach has attracted considerable interest for its real-time disease monitoring capability through repeated sample analysis. Several studies in CRC have revealed the potential for liquid biopsy application in a real clinical setting using circulating RNA/miRNA, circulating tumor cells (CTCs), exosomes, etc. However, Liquid biopsy still remains a challenge since there are currently no promising results with high specificity and specificity that might be employed as optimal circulatory biomarkers. Therefore, in this review, we conferred the plausible role of less explored liquid biopsy components like mitochondrial DNA (mtDNA), organoid model of CTCs, and circulating cancer-associated fibroblasts (cCAFs); which may allow researchers to develop improved strategies to unravel unfulfilled clinical requirements in CRC patients. Moreover, we have also discussed immunotherapy approaches to improve the prognosis of MSI (Microsatellite Instability) CRC patients using neoantigens and immune cells in the tumor microenvironment (TME) as a liquid biopsy approach in detail.

Tumor-Derived Extracellular Vesicles in Cancer Immunoediting and Their Potential as Oncoimmunotherapeutics

The tumor microenvironment (TME) within and around a tumor is a complex interacting mixture of tumor cells with various stromal cells, including endothelial cells, fibroblasts, and immune cells. In the early steps of tumor formation, the local microenvironment tends to oppose carcinogenesis, while with cancer progression, the microenvironment skews into a protumoral TME and the tumor influences stromal cells to provide tumor-supporting functions. The creation and development of cancer are dependent on escape from immune recognition predominantly by influencing stromal cells, particularly immune cells, to suppress antitumor immunity. This overall process is generally called immunoediting and has been categorized into three phases; elimination, equilibrium, and escape. Interaction of tumor cells with stromal cells in the TME is mediated generally by cell-to-cell contact, cytokines, growth factors, and extracellular vesicles (EVs). The least well studied are EVs (especially exosomes), which are nanoparticle-sized bilayer membrane vesicles released by many cell types that participate in cell/cell communication. EVs carry various proteins, nucleic acids, lipids, and small molecules that influence cells that ingest the EVs. Tumor-derived extracellular vesicles (TEVs) play a significant role in every stage of immunoediting, and their cargoes change from immune-activating in the early stages of immunoediting into immunosuppressing in the escape phase. In addition, their cargos change with different treatments or stress conditions and can be influenced to be more immune stimulatory against cancer. This review focuses on the emerging understanding of how TEVs affect the differentiation and effector functions of stromal cells and their role in immunoediting, from the early stages of immunoediting to immune escape. Consideration of how TEVs can be therapeutically utilized includes different treatments that can modify TEV to support cancer immunotherapy.

Predictive biomarkers of colon cancer immunotherapy: Present and future

Immunotherapy has revolutionized colon cancer treatment. Immune checkpoint inhibitors (ICIs) have shown clinical benefits for colon cancer patients, especially those with high microsatellite instability (MSI-H). In 2020, the US Food and Drug Administration (FDA)-approved ICI pembrolizumab as the first-line treatment for metastatic MSI-H colon cancer patients. Additionally, neoadjuvant immunotherapy has presented efficacy in treating early-stage colon cancer patients. Although MSI has been thought of as an effective predictive biomarker for colon cancer immunotherapy, only a small proportion of colon cancer patients were MSI-H, and certain colon cancer patients with MSI-H presented intrinsic or acquired resistance to immunotherapy. Thus, further search for predictive biomarkers to stratify patients is meaningful in colon cancer immunotherapy. Except for MSI, other biomarkers, such as PD-L1 expression level, tumor mutation burden (TMB), tumor-infiltrating lymphocytes (TILs), certain gut microbiota, ctDNA, and circulating immune cells were also proposed to be correlated with patient survival and ICI efficacy in some colon cancer clinical studies. Moreover, developing new diagnostic techniques helps identify accurate predictive biomarkers for colon cancer immunotherapy. In this review, we outline the reported predictive biomarkers in colon cancer immunotherapy and further discuss the prospects of technological changes for biomarker development in colon cancer immunotherapy.

Characterization of sialylation-related long noncoding RNAs to develop a novel signature for predicting prognosis, immune landscape, and chemotherapy response in colorectal cancer

Aberrant sialylation plays a key biological role in tumorigenesis and metastasis, including tumor cell survival and invasion, immune evasion, angiogenesis, and resistance to therapy. It has been proposed as a possible cancer biomarker and a potential therapeutic target of tumors. Nevertheless, the prognostic significance and biological features of sialylation-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) remain unclear. This study aimed to develop a novel sialylation-related lncRNA signature to accurately evaluate the prognosis of patients with CRC and explore the potential molecular mechanisms of the sialylation-related lncRNAs. Here, we identified sialylation-related lncRNAs using the Pearson correlation analysis on The Cancer Genome Atlas (TCGA) dataset. Univariate and stepwise multivariable Cox analysis were used to establish a signature based on seven sialylation-related lncRNAs in the TCGA dataset, and the risk model was validated in the Gene Expression Omnibus dataset. Kaplan-Meier curve analysis revealed that CRC patients in the low-risk subgroup had a better survival outcome than those in the high-risk subgroup in the training set, testing set, and overall set. Multivariate analysis demonstrated that the sialylation-related lncRNA signature was an independent prognostic factor for overall survival, progression-free survival, and disease-specific survival prediction. The sialylation lncRNA signature-based nomogram exhibited a robust prognostic performance. Furthermore, enrichment analysis showed that cancer hallmarks and oncogenic signaling were enriched in the high-risk group, while inflammatory responses and immune-related pathways were enriched in the low-risk group. The comprehensive analysis suggested that low-risk patients had higher activity of immune response pathways, greater immune cell infiltration, and higher expression of immune stimulators. In addition, we determined the sialylation level in normal colonic cells and CRC cell lines by flow cytometry combined with immunofluorescence, and verified the expression levels of seven lncRNAs using real-time quantitative polymerase chain reaction. Finally, combined drug sensitivity analysis using the Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, and Profiling Relative Inhibition Simultaneously in Mixtures indicated that the sialylation-related lncRNA signature could serve as a potential predictor for chemosensitivity. Collectively, this is the first sialylation lncRNA-based signature for predicting the prognosis, immune landscape, and chemotherapeutic response in CRC, and may provide vital guidance to facilitate risk stratification and optimize individualized therapy for CRC patients.

Development and validation of a cancer-associated fibroblast-derived lncRNA signature for predicting clinical outcomes in colorectal cancer

Cancer-associated fibroblasts (CAFs) are actively involved in cancer progression through generating extracellular matrix and orchestrating the crosstalk within the tumor microenvironment (TME). This study aimed to develop and validate a CAF-derived lncRNA (long non-coding RNA) (CAFDL) signature for predicting clinical outcomes in colorectal cancer (CRC). Clinical data and transcriptomic profiles of 2,320 patients with CRC from The Cancer Genome Atlas (TCGA)-COAD and TCGA-READ datasets and 16 Gene Expression Omnibus datasets were included in this study. CAFDLs were identified using weighted gene co-expression network analysis. The CAFDL signature was constructed using the least absolute shrinkage and selection operator analysis in the TCGA-CRC training set. Multiple CRC cohorts and pan-cancer cohorts were used to validated the CAFDL signature. Patients with high CAFDL scores had significantly worse overall survival and disease-free survival than patients with low CAFDL scores in all CRC cohorts. In addition, non-responders to fluorouracil, leucovorin, and oxaliplatin (FOLFOX)/fluorouracil, leucovorin, and irinotecan (FOLFIRI) chemotherapy, chemoradiotherapy, bevacizumab, and immune checkpoint inhibitors had significantly higher CAFDL scores compared with responders. Pan-cancer analysis showed that CAFDL had prognostic predictive power in multiple cancers such as lung adenocarcinoma, breast invasive carcinoma, stomach adenocarcinoma, and thyroid carcinoma. The CAFDL signature was positively correlated with transforming growth factor-beta (TGF-β) signaling, epithelial–mesenchymal transition, and angiogenesis pathways but negatively correlated with the expression of immune checkpoints such as PDCD1, CD274, and CTLA4. The CAFDL signature reflects CAF properties from a lncRNA perspective and effectively predicts clinical outcomes in CRC and across pan-cancer. The CAFDL signature can serve as a useful tool for risk stratification and provide new insights into the underlying mechanisms of CAFs in cancer immunity.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

Increased Expression of INHBA Is Correlated With Poor Prognosis and High Immune Infiltrating Level in Breast Cancer

Background: Inhibin, beta A (INHBA) is a member of the transforming growth factor-β superfamily and is associated with carcinogenesis and cancer progression in several types of human cancers. However, its significance in breast cancer has not been evaluated. Here, we investigated the prognostic value of INHBA and its correlation with tumor-infiltration immune cells in the microenvironment of breast cancer.

Methods: In this study, we analyzed the INHBA expression profile in the Oncomine database and Tumor Immune Estimation Resource 2.0 (TIMER2.0) site. Using Breast Cancer Gene-Expression Miner (bc-GenExMiner v4.7) tool and the UALCAN cancer database, we further evaluated the correlation of INHBA expression with clinicopathological factors in breast cancer. Then, we assessed the clinical prognostic value of INHBA using Kaplan–Meier Plotter and the PrognoScan databases. The correlations between INHBA and tumor-infiltrating immune cells were investigated via TIMER2.0. In addition, correlations between INHBA expression and gene markers of immune infiltrates were analyzed by TIMER2.0 and Gene Expression Profiling Interactive Analysis 2.

Results: Compared with the level in normal tissues, the INHBA mRNA expression was upregulated in different subtypes of breast cancer, and its expression was positively correlated with progesterone receptor, human epidermal growth factor receptor-2 status, and PAM50 subtypes but negatively related to age and basal-like status. The INHBA protein was also highly expressed in primary breast cancer and closely related to the pathological stage. Patients with high INHBA expression levels showed worse overall survival, relapse-free survival, and distant metastasis-free survival. Also, high INHBA expression was significantly associated with worse overall survival and relapse-free survival in positive lymph nodes. Of interest, INHBA expression was negatively correlated with infiltrating levels of activated NK cells, NKT, and CD4⁺ T cells but was positively correlated with tumor infiltration of CD8⁺ T cells, neutrophils, especially macrophages and cancer-associated fibroblasts. Moreover, INHBA expression showed strong correlations with various markers of monocytes/macrophages and cancer-associated fibroblasts.

Conclusion: High INHBA expression is correlated with poor prognosis and the infiltration of immune cells in the tumor microenvironment. These findings suggest that INHBA may be involved in immune escape and can serve as a potential biomarker of prognosis and tumor-infiltrating immune cells.