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.

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.

A susceptibility gene signature for ERBB2-driven mammary tumour development and metastasis in collaborative cross mice.

BACKGROUND: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. METHODS: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. FINDINGS: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. INTERPRETATION: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC. FUNDING: The U.S. Department of Defense (DoD) Breast Cancer Research Program (BCRP) (BC190820), United States; MCIN/AEI/10.13039/501100011039 (PID2020-118527RB-I00, PDC2021-121735-I00), the "European Union Next Generation EU/PRTR," the Regional Government of Castile and León (CSI144P20), European Union.

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.

An automatic weighting system for wild animals based in an artificial neural network: how to weigh wild animals without causing stress.

This paper proposes a novel and autonomous weighing system for wild animals. It allows evaluating changes in the body weight of animals in their natural environment without causing stress. The proposed system comprises a smart scale designed to estimate individual body weights and their temporal evolution in a bird colony. The system is based on computational intelligence, and offers valuable large amount of data to evaluate the relationship between long-term changes in the behavior of individuals and global change. The real deployment of this system has been for monitoring a breeding colony of lesser kestrels (Falco naumanni) in southern Spain. The results show that it is possible to monitor individual weight changes during the breeding season and to compare the weight evolution in males and females.

Berengeria Gil-Santana & Coletto-Silva, a junior synonym of Ectrichodiella Fracker & Bruner, with new records and taxonomic notes on Ectrichodiinae from Brazil, and with keys to Ectrichodiinae and Reduviinae genera of the New World (Hemiptera: Heteroptera: Reduviidae).

Berengeria Gil-Santana & Coletto-Silva, 2005 is considered a junior synonym of Ectrichodiella Fracker & Bruner, 1924. Ectrichodiella minima (Valdés, 1910) and E. rafaeli (Gil-Santana & Coletto-Silva, 2005), new. comb. are redescribed. Taxonomic notes on Brontostoma alboannulatum (Stål, 1860), B. discus (Burmeister, 1835), B. nanus Carpintero, 1980, B. rubrovenosum (Stål, 1860), and B. trux (Stål, 1859) are given. Brontostoma diringshofeni Gil-Santana & Baena, 2009, B. nanus, and Racelda robusta Bérenger & Gil-Santana, 2005 are recorded from Brazil for the first time. Keys to Ectrichodiinae and Reduviinae genera of the New World are presented.

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.

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.

A new subspecies of Ropalopus (Ropalopus) ungaricus (Herbst, 1784) from southern Spain, Ropalopus (Ropalopus) ungaricus occidentalis ssp. nov. (Coleoptera: Cerambycidae).

Ropalopus (Ropalopus) ungaricus occidentalis ssp. nov. is described, illustrated and compared with the other subspecies of Ropalopus (Ropalopus) ungaricus (Herbst, 1784). The new subspecies is close to Ropalopus (Ropalopus) ungaricus ossae Karpiski, Szczepaski Kruszelnicki, 2020. Data about the distribution, habitat and bionomy of the new subspecies and a keys to separation of the subspecies of Ropalopus (Ropalopus) ungaricus are given.

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.

Two new species of Pseudoniphargus (Amphipoda: Pseudoniphargidae) from southern Spain.

Two new species of subterranean water amphipod crustaceans of the genus Pseudoniphargus (Pseudoniphargidae) are described from gypsum caves of Andalusia, southern Spain. Both species share the extreme elongation of the male third uropod, a striking feature frequently reported in the genus and that seems to have arisen independently in several lineages. These findings raise the number of species of Pseudoniphargus known from the area to 17.

A redescription of the endemic Madagascan genus Tricompastes (Hemiptera: Heteroptera: Pentatomidae).

The endemic Madagascan genus Tricompastes Cachan, 1952 (Hemiptera: Heteroptera: Pentatomidae: Pentatominae: Triplatygini), containing a single species-Tricompastes gigas Cachan, 1952, is redescribed and illustrated, including first descriptions of male and female genitalia. First exact localities of the species are provided. Lectotype of T. gigas is designated.

Classification of Omalisidae based on molecular data and morphology, with description of Paradrilinae subfam. nov. (Coleoptera: Elateroidea).

Omalisidae, a species-poor family of elateroid beetles, are distributed mostly in the Mediterranean region. The morphology of females is modified due to neotenic development and the males share some traits with other neotenic lineages in Elateroidea, namely Drilini (Elateridae: Agrypninae) and Lyropaeinae (Lycidae). A molecular phylogeny was inferred from six omalisid species representing four genera and the previously published dataset of Elateroidea. The DNA based phylogeny suggests that small-bodied males, reduced pronotal carinae and missing elytral costae evolved independently in multiple elateroid lineages. The limits of Omalisidae are redefined and seven genera, i.e., Omalisus Geoffroy, 1762, Phaeopterus Costa, 1857, Thilmanus Gemminger, 1869, Euanoma Reitter, 1889, Pseudeuanoma Pic, 1901, Paradrilus Kiesenwetter, 1865 and Cimbrion Kazantsev, 2010, are currently placed in the family. Thilmaninae Kazantsev, 2005 and Paradrilus Kiesenwetter, 1865 are transferred from Drilini (Elateridae: Agrypninae) to Omalisidae and the Paradrilinae subfam. nov. is proposed. Paradrilus differs from other Omalisidae in prolonged cranium, wide robust prosternum with two apical processes and absent sharp edge of the pronotum. The morphology of Paradrilus is described in detail, illustrated and all taxa currently classified in Omalisidae are listed.