NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence.

BACKGROUND: Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. METHODS: We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H's (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. RESULTS: We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. CONCLUSIONS: The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

Cabergoline as a Novel Strategy for Post-Pregnancy Breast Cancer Prevention in Mice and Human.

Post-pregnancy breast cancer often carries a poor prognosis, posing a major clinical challenge. The increasing trend of later-life pregnancies exacerbates this risk, highlighting the need for effective chemoprevention strategies. Current options, limited to selective estrogen receptor modulators, aromatase inhibitors, or surgical procedures, offer limited efficacy and considerable side effects. Here, we report that cabergoline, a dopaminergic agonist, reduces the risk of breast cancer post-pregnancy in a Brca1/P53-deficient mouse model, with implications for human breast cancer prevention. We show that a single dose of cabergoline administered post-pregnancy significantly delayed the onset and reduced the incidence of breast cancer in Brca1/P53-deficient mice. Histological analysis revealed a notable acceleration in post-lactational involution over the short term, characterized by increased apoptosis and altered gene expression related to ion transport. Over the long term, histological changes in the mammary gland included a reduction in the ductal component, decreased epithelial proliferation, and a lower presence of recombinant Brca1/P53 target cells, which are precursors of tumors. These changes serve as indicators of reduced breast cancer susceptibility. Additionally, RNA sequencing identified gene expression alterations associated with decreased proliferation and mammary gland branching. Our findings highlight a mechanism wherein cabergoline enhances the protective effect of pregnancy against breast cancer by potentiating postlactational involution. Notably, a retrospective cohort study in women demonstrated a markedly lower incidence of post-pregnancy breast cancer in those treated with cabergoline compared to a control group. Our work underscores the importance of enhancing postlactational involution as a strategy for breast cancer prevention, and identifies cabergoline as a promising, low-risk option in breast cancer chemoprevention. This strategy has the potential to revolutionize breast cancer prevention approaches, particularly for women at increased risk due to genetic factors or delayed childbirth, and has wider implications beyond hereditary breast cancer cases.

Identification of Genomic Regions Implicated in Susceptibility to Schistosoma mansoni Infection in a Murine Backcross Genetic Model.

Only a small number of infected people are highly susceptible to schistosomiasis, showing high levels of infection or severe liver fibrosis. The susceptibility to schistosome infection is influenced by genetic background. To assess the genetic basis of susceptibility and identify the chromosomal regions involved, a backcross strategy was employed to generate high variation in schistosomiasis susceptibility. This strategy involved crossing the resistant C57BL/6J mouse strain with the susceptible CBA/2J strain. The resulting F1 females (C57BL/6J × CBA/2J) were then backcrossed with CBA/2J males to generate the backcross (BX) cohort. The BX mice exhibited a range of phenotypes, with disease severity varying from mild to severe disease, lacking a fully resistant group. We observed four levels of infection intensity using cluster and principal component analyses and K-means based on parasitological, pathological, and immunological trait measurements. The mice were genotyped with 961 informative SNPs, leading to the identification of 19 new quantitative trait loci (QTL) associated with parasite burden, liver lesions, white blood cell populations, and antibody responses. Two QTLs located on chromosomes 15 and 18 were linked to the number of granulomas, liver lesions, and IgM levels. The corresponding syntenic human regions are located in chromosomes 8 and 18. None of the significant QTLs had been reported previously.

NCAPH Drives Breast Cancer Progression and Identifies a Gene Signature that Predicts Luminal A Tumor Recurrence.

Despite their generally favorable prognosis, luminal A tumors paradoxically pose the highest ten-year recurrence risk among breast cancers. From those that relapse, a quarter of them do it within five years after diagnosis. Identifying such patients is crucial, as long-term relapsers could benefit from extended hormone therapy, whereas early relapsers may require aggressive treatment. In this study, we demonstrate that NCAPH plays a role in the pathogenesis of luminal A breast cancer, contributing to its adverse progression in vitro and in vivo. Furthermore, we reveal that a signature of intratumoral gene expression, associated with elevated levels of NCAPH, serves as a potential marker to identify patients facing unfavorable progression of luminal A breast cancer. Indeed, transgenic mice overexpressing NCAPH generated breast tumors with long latency, and in MMTV-NCAPH/ErbB2+ double-transgenic mice, the luminal tumors formed were more aggressive. In addition, high intratumoral levels of Ncaph were associated with worse breast cancer evolution and poor response to chemotherapy in a cohort of genetically heterogeneous transgenic mice generated by backcrossing. In this cohort of mice, we identified a series of transcripts associated with elevated intratumoral levels of NCAPH, which were linked to adverse progression of breast cancer in both mice and humans. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) multivariate regression analysis on this series of transcripts, we derived a ten-gene risk score. This score is defined by a gene signature (termed Gene Signature for Luminal A 10 or GSLA10) that correlates with unfavorable progression of luminal A breast cancer. The GSLA10 signature surpassed the Oncotype DX signature in discerning tumors with unfavorable outcomes (previously categorized as Luminal A by PAM50) across three independent human cohorts. This GSLA10 signature aids in identifying patients with Luminal A tumors displaying adverse prognosis, who could potentially benefit from personalized treatment strategies.

The Role of GAB1 in Cancer.

GRB2-associated binder 1 (GAB1) is the inaugural member of the GAB/DOS family of pleckstrin homology (PH) domain-containing proteins. Upon receiving various stimuli, GAB1 transitions from the cytoplasm to the membrane where it is phosphorylated by a range of kinases. This event recruits SH2 domain-containing proteins like SHP2, PI3K's p85 subunit, CRK, and others, thereby activating distinct signaling pathways, including MAPK, PI3K/AKT, and JNK. GAB1-deficient embryos succumb in utero, presenting with developmental abnormalities in the heart, placenta, liver, skin, limb, and diaphragm myocytes. Oncogenic mutations have been identified in the context of cancer. GAB1 expression levels are disrupted in various tumors, and elevated levels in patients often portend a worse prognosis in multiple cancer types. This review focuses on GAB1's influence on cellular transformation particularly in proliferation, evasion of apoptosis, metastasis, and angiogenesis-each of these processes being a cancer hallmark. GAB1 also modulates the resistance/sensitivity to antitumor therapies, making it a promising target for future anticancer strategies.

AI-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma.

INTRODUCTION: Risk stratification of cutaneous squamous cell carcinoma (CSCC) is essential for managing patients. Artificial intelligence and machine learning might help stratify patients with CSCC by risk using more than solely clinical and histopathological factors. METHODS: A retrospective cohort of 104 CSCCs excised with clear margins was retrieved. Clinical and histopathological risk factors were evaluated. Hematoxylin and eosin-stained slides were scanned and analyzed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified CSCC into clusters of differential prognosis. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated and compared with results obtained with the Brigham and Women's Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analyzed. RESULTS: There were no differences among CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.92 for local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16% with the combined approach. CONCLUSION: CMRS is helpful for CSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for high-risk CSCC patients.

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy.

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

Evolutionary Origins of Metabolic Reprogramming in Cancer.

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. These changes are not specific to tumors but also take place during the physiological growth of tissues. Indeed, the cellular and tissue mechanisms present in the tumor have their physiological counterpart in the repair of tissue lesions and wound healing. These molecular mechanisms have been acquired during metazoan evolution, first to eliminate the infection of the tissue injury, then to enter an effective regenerative phase. Cancer itself could be considered a phenomenon of antagonistic pleiotropy of the genes involved in effective tissue repair. Cancer and tissue repair are complex traits that share many intermediate phenotypes at the molecular, cellular, and tissue levels, and all of these are integrated within a Systems Biology structure. Complex traits are influenced by a multitude of common genes, each with a weak effect. This polygenic component of complex traits is mainly unknown and so makes up part of the missing heritability. Here, we try to integrate these different perspectives from the point of view of the metabolic changes observed in cancer.

iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers.

BACKGROUND: The development of precision medicine is essential for personalized treatment and improved clinical outcome, whereas biomarkers are critical for the success of precision therapies. AIM: To investigate whether iCEMIGE (integration of CEll-morphometrics, MIcro biome, and GEne biomarker signatures) improves risk stratification of breast cancer (BC) patients. METHODS: We used our recently developed machine learning technique to identify cellular morphometric biomarkers (CMBs) from the whole histological slide images in The Cancer Genome Atlas (TCGA) breast cancer (TCGA-BRCA) cohort. Multivariate Cox regression was used to assess whether cell-morphometrics prognosis score (CMPS) and our previously reported 12-gene expression prognosis score (GEPS) and 15-microbe abundance prognosis score (MAPS) were independent prognostic factors. iCEMIGE was built upon the sparse representation learning technique. The iCEMIGE scoring model performance was measured by the area under the receiver operating characteristic curve compared to CMPS, GEPS, or MAPS alone. Nomogram models were created to predict overall survival (OS) and progress-free survival (PFS) rates at 5- and 10-year in the TCGA-BRCA cohort. RESULTS: We identified 39 CMBs that were used to create a CMPS system in BCs. CMPS, GEPS, and MAPS were found to be significantly independently associated with OS. We then established an iCEMIGE scoring system for risk stratification of BC patients. The iGEMIGE score has a significant prognostic value for OS and PFS independent of clinical factors (age, stage, and estrogen and progesterone receptor status) and PAM50-based molecular subtype. Importantly, the iCEMIGE score significantly increased the power to predict OS and PFS compared to CMPS, GEPS, or MAPS alone. CONCLUSION: Our study demonstrates a novel and generic artificial intelligence framework for multimodal data integration toward improving prognosis risk stratification of BC patients, which can be extended to other types of cancer.

Chloroquine-Induced DNA Damage Synergizes with Nonhomologous End Joining Inhibition to Cause Ovarian Cancer Cell Cytotoxicity.

Ovarian cancer (OC) is the most lethal gynecological malignancy; therefore, more effective treatments are urgently needed. We recently reported that chloroquine (CQ) increased reactive oxygen species (ROS) in OC cell lines (OCCLs), causing DNA double-strand breaks (DSBs). Here, we analyzed whether these lesions are repaired by nonhomologous end joining (NHEJ), one of the main pathways involved in DSB repair, and if the combination of CQ with NHEJ inhibitors (NHEJi) could be effective against OC. We found that NHEJ inhibition increased the persistence of γH2AX foci after CQ-induced DNA damage, revealing an essential role of this pathway in the repair of the lesions. NHEJi decreased the proliferation of OCCLs and a strong in vitro synergistic effect on apoptosis induction was observed when combined with CQ. This effect was largely abolished by the antioxidant N-Acetyl-L-cysteine, revealing the critical role of ROS and DSB generation in CQ/NHEJi-induced lethality. We also found that the NHEJ efficiency in OCCLs was not affected by treatment with Panobinostat, a pan-histone deacetylase inhibitor that also synergizes with CQ in OCCLs by impairing homologous recombination. Accordingly, the triple combination of CQ-NHEJi-Panobinostat exerted a stronger in vitro synergistic effect. Altogether, our data suggest that the combination of these drugs could represent new therapeutic strategies against OC.

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer.

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.

Overcoming Resistance to Immunotherapy in Advanced Cutaneous Squamous Cell Carcinoma.

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans, and is now responsible for as many deaths as melanoma. Immunotherapy has changed the therapeutic landscape of advanced CSCC after the FDA approval of anti-PD1 molecules for the treatment of locally advanced and metastatic CSCC. However, roughly 50% of patients will not respond to this systemic treatment and even those who do respond can develop resistance over time. The etiologies of primary and secondary resistance to immunotherapy involve changes in the neoplastic cells and the tumor microenvironment. Indirect modulation of immune system activation with new therapies, such as vaccines, oncolytic viruses, and new immunotherapeutic agents, and direct modulation of tumor immunogenicity using other systemic treatments or radiotherapy are now under evaluation in combined regimens. The identification of predictors of response is an important area of research. In this review, we focus on the features associated with the response to immunotherapy, and the evaluation of combination treatments and new molecules, a more thorough knowledge of which is likely to improve the survival of patients with advanced CSCC.

Distinct Clinical Impact and Biological Function of Angiopoietin and Angiopoietin-like Proteins in Human Breast Cancer.

Secreted angiopoietin/angiopoietin-like (ANGPT/ANGPTL) proteins are involved in many biological processes. However, the role of these proteins in human breast cancers (BCs) remains largely unclear. Here, we conducted integrated omics analyses to evaluate the clinical impact of ANGPT/ANGPTL proteins and to elucidate their biological functions. In BCs, we identified rare mutations in ANGPT/ANGPTL genes, frequent gains of ANGPT1, ANGPT4, and ANGPTL1, and frequent losses of ANGPT2, ANGPTL5, and ANGPTL7, but observed that ANGPTL1, 2, and 4 were robustly downregulated in multiple datasets. The expression levels of ANGPTL1, 5, and 8 were positively correlated with overall survival (OS), while the expression levels of ANGPTL4 were negatively correlated with OS. Additionally, the expression levels of ANGPTL1 and 7 were positively correlated with distant metastasis-free survival (DMFS), while the expression levels of ANGPT2 and ANGPTL4 were negatively correlated with DMFS. The prognostic impacts of ANGPT/ANGPTL genes depended on the molecular subtypes and on clinical factors. We discovered that various ANGPT/ANGPTL genes were co-expressed with various genes involved in different pathways. Finally, with the exception of ANGPTL3, the remaining genes showed significant correlations with cancer-associated fibroblasts, endothelial cells, and microenvironment score, whereas only ANGPTL6 was significantly correlated with immune score. Our findings provide strong evidence for the distinct clinical impact and biological function of ANGPT/ANGPTL proteins, but the question of whether some of them could be potential therapeutic targets still needs further investigation in BCs.

Viruses and Skin Cancer.

Advances in virology and skin cancer over recent decades have produced achievements that have been recognized not only in the field of dermatology, but also in other areas of medicine. They have modified the therapeutic and preventive solutions that can be offered to some patients and represent a significant step forward in our knowledge of the biology of skin cancer. In this paper, we review the viral agents responsible for different types of skin cancer, especially for solid skin tumors. We focus on human papillomavirus and squamous cell cancers, Merkel cell polyomavirus and Merkel cell carcinoma, and human herpesvirus 8 and Kaposi's sarcoma.

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan-Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.

Stromal SNAI2 Is Required for ERBB2 Breast Cancer Progression.

SNAI2 overexpression appears to be associated with poor prognosis in breast cancer, yet it remains unclear in which breast cancer subtypes this occurs. Here we show that excess SNAI2 is associated with a poor prognosis of luminal B HER2+/ERBB2+ breast cancers in which SNAI2 expression in the stroma but not the epithelium correlates with tumor proliferation. To determine how stromal SNAI2 might influence HER2+ tumor behavior, Snai2-deficient mice were crossed with a mouse line carrying the ErbB2/Neu protooncogene to generate HER2+/ERBB2+ breast cancer. Tumors generated in this model expressed SNAI2 in the stroma but not the epithelium, allowing for the role of stromal SNAI2 to be studied without interference from the epithelial compartment. The absence of SNAI2 in the stroma of HER2+/ERBB2+ tumors is associated with: (i) lower levels of cyclin D1 (CCND1) and reduced tumor epithelium proliferation; (ii) higher levels of AKT and a lower incidence of metastasis; (iii) lower levels of angiopoietin-2 (ANGPT2), and more necrosis. Together, these results indicate that the loss of SNAI2 in cancer-associated fibroblasts limits the production of some cytokines, which influences AKT/ERK tumor signaling and subsequent proliferative and metastatic capacity of ERBB2+ breast cancer cells. Accordingly, SNAI2 expression in the stroma enhanced the tumorigenicity of luminal B HER2+/ERBB2+ breast cancers. This work emphasizes the importance of stromal SNAI2 in breast cancer progression and patients' prognosis. SIGNIFICANCE: Stromal SNAI2 expression enhances the tumorigenicity of luminal B HER2+ breast cancers and can identify a subset of patients with poor prognosis, making SNAI2 a potential therapeutic target for this disease. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/23/5216/F1.large.jpg.

Cutaneous Squamous Cell Carcinoma: From Biology to Therapy.

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans and its incidence continues to rise. Although CSCC usually display a benign clinical behavior, it can be both locally invasive and metastatic. The signaling pathways involved in CSCC development have given rise to targetable molecules in recent decades. In addition, the high mutational burden and increased risk of CSCC in patients under immunosuppression were part of the rationale for developing the immunotherapy for CSCC that has changed the therapeutic landscape. This review focuses on the molecular basis of CSCC and the current biology-based approaches of targeted therapies and immune checkpoint inhibitors. Another purpose of this review is to explore the landscape of drugs that may induce or contribute to the development of CSCC. Beginning with the pathogenetic basis of these drug-induced CSCCs, we move on to consider potential therapeutic opportunities for overcoming this adverse effect.

MicroRNA Dysregulation in Cutaneous Squamous Cell Carcinoma.

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans and it can be locally invasive and metastatic to distant sites. MicroRNAs (miRNAs or miRs) are endogenous, small, non-coding RNAs of 19-25 nucleotides in length, that are involved in regulating gene expression at a post-transcriptional level. MicroRNAs have been implicated in diverse biological functions and diseases. In cancer, miRNAs can proceed either as oncogenic miRNAs (onco-miRs) or as tumor suppressor miRNAs (oncosuppressor-miRs), depending on the pathway in which they are involved. Dysregulation of miRNA expression has been shown in most of the tumors evaluated. MiRNA dysregulation is known to be involved in the development of cutaneous squamous cell carcinoma (CSCC). In this review, we focus on the recent evidence about the role of miRNAs in the development of CSCC and in the prognosis of this form of skin cancer.