AcornHRD: an HRD algorithm highly associated with anthracycline-based neoadjuvant chemotherapy in breast cancer in China.

PURPOSE: Our study aimed to develop and validate a homologous recombination deficiency (HRD) scoring algorithm in the Chinese breast cancer population. METHODS AND MATERIALS: Ninety-six in-house breast cancer (BC) samples and 6 HRD-positive standard cells were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ~ 1X WGS. We constructed an algorithm named AcornHRD for HRD score calculated based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-based neoadjuvant treatment outcomes. RESULTS: A 100-kb window was defined as the optimal size using 41 in-house cases and the TCGA dataset. HRD score high threshold was determined as HRD score ≥ 10 using 55 in-house BCs with BRCA mutation to achieve a 95% BRCA-positive agreement rate. Furthermore, the HRD status agreement rate of AcornHRD is 100%, while the ShallowHRD is 60% in standard cells. BRCA mutation was significantly associated with a high HRD score evaluated by AcornHRD and ShallowHRD (p = 0.008 and p = 0.003, respectively) in the TCGA dataset. However, AcornHRD showed a higher positive agreement rate than did the ShallowHRD algorithm (70% vs 60%). In addition, the BRCA-positive agreement rate of AcornHRD was superior to that of ShallowHRD (87% vs 13%) in the clinical cohort. Importantly, the high HRD score assessed by AcornHRD was significantly correlated with a residual cancer burden score of 0 or 1 (RCB0/1). Besides, the HRD-positive group was more likely to respond to anthracycline-based chemotherapy than the HRD-negative group (pCR [OR = 9.5, 95% CI 1.11-81.5, p = 0.040] and RCB0/1 [OR = 10.29, 95% CI 2.02-52.36, p = 0.005]). CONCLUSION: Using the AcornHRD algorithm evaluation, our analysis demonstrated the high performance of the LCNA genomic signature for HRD detection in breast cancers.

ACSS2 enables melanoma cell survival and tumor metastasis by negatively regulating the Hippo pathway.

Introduction: Acetyl-CoA synthetase 2 (ACSS2), one of the enzymes that catalyze the conversion of acetate to acetyl-CoA, has been proved to be an oncogene in various cancers. However, the function of ACSS2 is still largely a black box in melanoma. Methods: The ACSS2 expression was detected in melanoma cells and melanocytes at both protein and mRNA levels. Cell viability, apoptosis, migration and invasion were investigated after ACSS2 knockdown. RNA sequencing (RNA-Seq) technology was employed to identify differentially expressed genes caused by ACSS2 knockdown, which were then verified by immunoblotting analysis. Animal experiments were further performed to investigate the influence of ACSS2 on tumor growth and metastasis in vivo. Results: Firstly, we found that ACSS2 was upregulated in most melanoma cell lines compared with melanocytes. In addition, ACSS2 knockdown dramatically suppressed melanoma cell migration and invasion, whereas promoted cell apoptosis in response to endoplasmic reticulum (ER) stress. Furthermore, tumor growth and metastasis were dramatically suppressed by ACSS2 knockdown in vivo. RNA-Seq suggested that the Hippo pathway was activated by ACSS2 knockdown, which was forwardly confirmed by Western blotting and rescue experiments. Taken together, we demonstrated that ACSS2 enables melanoma cell survival and tumor metastasis via the regulation of the Hippo pathway. Discussion: In summary, this study demonstrated that ACSS2 may promote the growth and metastasis of melanoma by negatively regulating the Hippo pathway. Targeting ACSS2 may be a promising target for melanoma treatment.

SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma.

Melanoma, arising from the malignant transformation of melanocytes, stands as the most lethal type of skin cancer. While significant strides have been made in targeted therapy and immunotherapy, substantially enhancing therapeutic efficacy, the prognosis for melanoma patients remains unoptimistic. SIRT7, a nuclear-localized deacetylase, plays a pivotal role in maintaining cellular homeostasis and adapting to external stressors in melanoma, with its activity closely tied to intracellular nicotinamide adenine dinucleotide (NAD+). However, its involvement in adaptive resistance to targeted therapy remains unclear. Herein, we unveil that up-regulated SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma. Initially, we observed a significant increase of SIRT7 expression in publicly available datasets following targeted therapy within a short duration. In consistent, we found elevated SIRT7 expression in melanoma cells subjected to BRAF or MEK inhibitors in vitro. The up-regulation of SIRT7 expression was also confirmed in xenograft tumors in mice after targeted therapy in vivo. Furthermore, we proved that SIRT7 deficiency led to decreased cell viability upon prolonged exposure to BRAF or MEK inhibitors, accompanied by an increase in cell apoptosis. Mechanistically, SIRT7 deficiency restrained the upregulation of genes associated with mitochondrial biogenesis and intracellular ATP levels in response to targeted therapy treatment in melanoma cells. Ultimately, we proved that SIRT7 deficieny could sensitize BRAF-mutant melanoma cells to MAPK inhibition targeted therapy in vivo. In conclusion, our findings underscore the role of SIRT7 in fostering adaptive resistance to targeted therapy through the facilitation of mitochondrial biogenesis. Targeting SIRT7 emerges as a promising strategy to overcome MAPK inhibitor adaptive resistance in melanoma.

Phase 2 Study of Preoperative Tislelizumab in Combination with Low-dose Nab-Paclitaxel in Patients with Muscle-invasive Bladder Cancer.

BACKGROUND AND OBJECTIVE: Combinations of immune checkpoint inhibitors and nab-paclitaxel have achieved significant therapeutic effects in the treatment of advanced urothelial carcinoma. Our aim was to assess the efficacy and safety of tislelizumab combined with low-dose nab-paclitaxel in patients with muscle-invasive bladder cancer (MIBC). METHODS: TRUCE-01 was a single-arm phase 2 study that included 62 patients with T2-4a N0/X M0 MIBC tumors with predominant urothelial carcinoma histology. Eligible patients received three 21-d cycles of intravenous 200 mg tislelizumab on day 1 plus intravenous 200 mg nab-paclitaxel on day 2, followed by surgical assessment. The primary study endpoint was a clinical complete response (cCR). Treatment-related adverse event (TRAE) profiles were recorded according to Common Terminology Criteria for Adverse Events version 5.0. KEY FINDINGS AND LIMITATIONS: The safety analysis included all 62 patients and the efficacy analysis included 48 patients. The primary efficacy endpoint (cCR) was met by 25 patients (52%) patients. Among the 62 patients in the safety analysis, six (9.7%) had grade ≥3 TRAEs. CONCLUSIONS: Tislelizumab combined with low-dose nab-paclitaxel showed promising antitumor effectiveness and was generally well tolerated, which makes it an excellent preoperative therapy option for MIBC. PATIENT SUMMARY: We found that a combination of the drugs tislelizumab and low-dose nab-paclitaxel had satisfactory efficacy and safety for preoperative treatment of muscle-invasive bladder cancer.

Classification of multiple primary lung cancer in patients with multifocal lung cancer: assessment of a machine learning approach using multidimensional genomic data.

Background: Multiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment. Methods: A total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors. Results: We found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p <.01). Conclusion: These data provide novel evidence of MPLC-specific genomic characteristics and demonstrate that our one-step molecular classifier can accurately classify multifocal lung tumors as MPLC or IM, which suggested that broad panel NGS may be a useful tool for assisting with differential diagnoses.

Harnessing Synchronous Photothermal and Photocatalytic Effects of Substoichiometric MoO3-x Nanoparticle-Decorated Membranes for Clean Water Generation.

Solar-driven interfacial evaporation provides a promising pathway for sustainable freshwater and energy generation. However, developing highly efficient photothermal and photocatalytic nanomaterials is challenging. Herein, substoichiometric molybdenum oxide (MoO3-x) nanoparticles are synthesized via step-by-step reduction treatment of l-cysteine under mild conditions for simultaneous photothermal conversion and photocatalytic reactions. The MoO3-x nanoparticles of low reduction degree are decorated on hydrophilic cotton cloth to prepare a MCML evaporator toward rapid water production, pollutant degradation, as well as electricity generation. The obtained MCML evaporator has a strong local light-to-heat effect, which can be attributed to excellent photothermal conversion via the local surface plasmon resonance effect in MoO3-x nanoparticles and the low heat loss of the evaporator. Meanwhile, the rich surface area of MoO3-x nanoparticles and the localized photothermal effect together effectively accelerate the photocatalytic degradation reaction of the antibiotic tetracycline. With the benefit of these advantages, the MCML evaporator attains a superior evaporation rate of 4.14 kg m-2 h-1, admirable conversion efficiency of 90.7%, and adequate degradation efficiency of 96.2% under 1 sun irradiation. Furthermore, after being rationally assembled with a thermoelectric module, the hybrid device can be employed to generate 1.0 W m-2 of electric power density. This work presents an effective complementary strategy for freshwater production and sewage treatment as well as electricity generation in remote and off-grid regions.

Machine-learning-based classification of diffuse large B-cell lymphoma patients by a 7-mRNA signature enriched with immune infiltration and cell cycle / Clasificación basada en aprendizaje automático de pacientes con linfoma difuso de células B grandes mediante una firma de 7 ARNm enriquecida con infiltración inmune y ciclo celular

Background: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment. Methods: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes. Meanwhile, univariate and multivariate Cox regression analyses were used to evaluate independent prognostic factors of DLBCL. Finally, the prognostic model, including some key genes screened by Lasso regression, Random Forest algorithm, and point-biserial correlation, was constructed by an optimal classifier from seven machine learning algorithms and validated by another three external datasets (GSE34171, GSE87371, GSE31312). Results: Comprehensive genomic analysis of 1,143 DLBCL samples identify 2 molecularly, prognostically relevant subtypes: immune-enriched (IME) and cell-cycle-enriched (CCE). Then a new predictive model including seven key genes (SERPING1, TIMP2, NME1, DCTPP1, RFC4, POLE2, and SNRPD1) was developed with high prediction accuracy (88.6%) and strong predictive power (AUC = 0.973) based on the Support Vector Machine (SVM) algorithm in 414 patients from GSE10846. The predictive power was similar in another three testing sets (HR > 1.400, p < 0.05). Conclusion: This model could evaluate survival independently with strong predictive power compared with other clinical risk factors. Our study constructed a reliable model to predict two new subtypes of DLBCL patients, which could guide the implementation of individualized treatment.(AU)

Clinical effectiveness of a multitarget urine DNA test for urothelial carcinoma detection: a double-blinded, multicenter, prospective trial.

Urine-based testing is promising for noninvasive diagnosis of urothelial carcinoma (UC) but has suboptimal sensitivity for early-stage tumors. Herein, we developed a multitarget urine tumor DNA test, UI-Seek, for UC detection and evaluated its clinical feasibility. The prediction model was developed in a retrospective cohort (n = 382), integrating assays for FGFR3 and TERT mutations and aberrant ONECUT2 and VIM methylation to generate a UC-score. The test performance was validated in a double-blinded, multicenter, prospective trial (n = 947; ChiCTR2300076543) and demonstrated a sensitivity of 91.37% and a specificity of 95.09%. The sensitivity reached 75.81% for low-grade Ta tumors and exceeded 93% in high-grade Ta and higher stages (T1 to T4). Simultaneous identification of both bladder and upper urinary tract tumors was enabled with sensitivities exceeding 90%. No significant confounding effects were observed regarding benign urological diseases or non-UC malignancies. The test showed improved sensitivities over urine cytology, the NMP22 test, and UroVysion FISH alongside comparable specificities. The single-target accuracy was greater than 98% as confirmed by Sanger sequencing. Post-surgery UC-score decreased in 97.7% of subjects. Overall, UI-Seek demonstrated robust performance and considerable potential for the early detection of UC.

Unique fluorescent probe for the recognition of late apoptosis via translocation from plasma membrane to nucleus.

Cell apoptosis is a crucial physiological process playing central roles in key biological and pathological activities. However, the current fluorescent probes for the detection of late apoptosis were "off-on" probes, which were facilely interfered by false positive signals caused by inhomogeneous staining and other factors. Herein, a unique fluorescent probe (NPn) discriminating late apoptosis from early apoptosis and heathy status with two different sets of fluorescent signals have been prepared, to overcome the possible false positive signals. NPn was designed impermeable to biomembranes and simultaneously with high affinity to DNA/RNA, which localized on the plasma membranes of living and early apoptotic cells, while relocated to the nucleus in late apoptotic cells. The hydrophilic amine unit and small ion radius were responsive for its membrane impermeability, which was confirmed with two control molecules without amine group. Using the probe, we have successfully evaluated the cell apoptosis induced by ultraviolet irradiation, rotenone, colchicine, and paclitaxel, demonstrating its potential application in biological researches.

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis.

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.g., image, text, speech, genetic data, physiological signals) is imperative to facilitate a comprehensive disease analysis, a topic of burgeoning interest among both researchers and clinicians in recent times. Hence, there exists a pressing need to synthesize the latest strides in multi-modal data and AI technologies in the realm of medical diagnosis. In this paper, we narrow our focus to five specific disorders (Alzheimer's disease, breast cancer, depression, heart disease, epilepsy), elucidating advanced endeavors in their diagnosis and treatment through the lens of artificial intelligence. Our survey not only delineates detailed diagnostic methodologies across varying modalities but also underscores commonly utilized public datasets, the intricacies of feature engineering, prevalent classification models, and envisaged challenges for future endeavors. In essence, our research endeavors to contribute to the advancement of diagnostic methodologies, furnishing invaluable insights for clinical decision making.

DNA damage response alterations in clear cell renal cell carcinoma: clinical, molecular, and prognostic implications.

BACKGROUND: DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic responses. Nonetheless, the characteristics and significance of DDR alterations in clear cell renal cell carcinoma (ccRCC) remain undefined. This study aimed to explore the predictive role, molecular mechanism, and tumor immune profile of DDR genes in ccRCC. METHODS: We prospectively sequenced 757 tumors and matched blood DNA samples from Chinese patients with ccRCC using next-generation sequencing (NGS) and analyzed data from 537 patients from The Cancer Genome Atlas (TCGA). A comprehensive analysis was performed. RESULTS: Fifty-two percent of Chinese patients with ccRCC harbored DDR gene mutations and 57% of TCGA patients. The immunotherapy treatment prognosis of patients with DDR gene mutations was superior to that of patients without DDR gene mutations (p = 0.047). DDR gene mutations were associated with more gene mutations and a higher tumor mutation load (TMB, p < 0.001). Moreover, patients with DDR gene mutations have a distinct mutational signature compared with those with wild-type DDR. Furthermore, the DDR-mut group had elevated neoantigen load (including single-nucleotide variants (SNV) and indel neoantigen load, p = 0.037 and p = 0.002, respectively), TCR Shannon (p = 0.025), and neutrophils (p = 0.010). DDR gene mutations exhibited a distinct immune profile with significantly higher expression levels of TNFSF9, CD70, ICAM1, and indoleamine-2,3-dioxygenase (IDO) and lower expression levels of VTCN1 and IL12A. CONCLUSIONS: Our data suggest that the detection of somatic mutations in DDR genes can predict the efficacy of immunotherapy in patients with ccRCC. Furthermore, we revealed the unique molecular and immune mechanisms underlying ccRCC with DDR gene mutations.

Analysis of the Genetic Characteristics and Metastatic Pathways of G1 and G2 Colorectal Neuroendocrine Neoplasms.

Objective: G1 and G2 colorectal neuroendocrine neoplasms (NENs) are a group of rare and indolent diseases. We aimed to delineate their genetic characteristics and explore their metastatic mechanisms. Methods: We used next-generation sequencing technology for targeted sequencing for 54 patients with G1 and G2 colorectal NENs. We delineated their genetic features and compared the genetic characteristics between metastatic NENs and nonmetastatic NENs. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was utilized to explore their abnormal pathways and study their potential metastatic mechanisms. Results: We collected 23 metastatic NENs and 31 nonmetastatic NENs. In the whole cohort, the common mutated genes were NCOR2, BRD4, MDC1, ARID1A, AXIN2, etc. The common copy number variations (CNVs) included amplification of HIST1H3D, amplification of HIST1H3E, and loss of PTEN. The KEGG enrichment analysis revealed that PI3K-Akt, MAPK, and Rap1 were the major abnormal pathways. There were significantly different genetic features between metastatic NENs and nonmetastatic NENs. The metastatic NENs shared only 47 (22.5%) mutated genes and 6 (13.3%) CNVs with nonmetastatic NENs. NCOR2, BRD4, CDKN1B, CYP3A5, and EIF1AX were the commonly mutated genes in metastatic NENs, while NCOR2, MDC1, AXIN2, PIK3C2G, and PTPRT were the commonly mutated genes in nonmetastatic NENs. Metastatic NENs presented a significantly higher proportion of abnormal pathways of cell senescence (56.5% vs 25.8%, P = .022) and lysine degradation (43.5% vs 16.1%, P = .027) than nonmetastatic NENs. Conclusion: G1 and G2 colorectal NENs are a group of heterogeneous diseases that might obtain an increased invasive ability through aberrant cell senescence and lysine degradation pathways.

Tumorous IRE1α facilitates CD8+T cells-dependent anti-tumor immunity and improves immunotherapy efficacy in melanoma.

BACKGROUND: Tumor cells frequently suffer from endoplasmic reticulum (ER) stress. Previous studies have extensively elucidated the role of tumorous unfolded protein response in melanoma cells, whereas the effect on tumor immunology and the underlying mechanism remain elusive. METHODS: Bioinformatics, biochemical assays and pre-clinical mice model were employed to demonstrate the role of tumorous inositol-requiring transmembrane kinase/endoribonuclease 1α (IRE1α) in anti-tumor immunity and the underlying mechanism. RESULTS: We firstly found that IRE1α signaling activation was positively associated with the feature of tumor-infiltrating lymphocytes. Then, pharmacological ER stress induction by HA15 exerted prominent anti-tumor effect in immunocompetent mice and was highly dependent on CD8+T cells, paralleled with the reshape of immune cells in tumor microenvironment via tumorous IRE1α-XBP1 signal. Subsequently, tumorous IRE1α facilitated the expression and secretion of multiple chemokines and cytokines via XBP1-NF-κB axis, leading to increased infiltration and anti-tumor capacity of CD8+T cells. Ultimately, pharmacological induction of tumorous ER stress by HA15 brought potentiated therapeutic effect along with anti-PD-1 antibody on melanoma in vivo. CONCLUSIONS: Tumorous IRE1α facilitates CD8+T cells-dependent anti-tumor immunity and improves immunotherapy efficacy by regulating chemokines and cytokines via XBP1-NF-κB axis. The combination of ER stress inducer and anti-PD-1 antibody could be promising for increasing the efficacy of melanoma immunotherapy.

Machine-learning-based classification of diffuse large B-cell lymphoma patients by a 7-mRNA signature enriched with immune infiltration and cell cycle.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment. METHODS: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes. Meanwhile, univariate and multivariate Cox regression analyses were used to evaluate independent prognostic factors of DLBCL. Finally, the prognostic model, including some key genes screened by Lasso regression, Random Forest algorithm, and point-biserial correlation, was constructed by an optimal classifier from seven machine learning algorithms and validated by another three external datasets (GSE34171, GSE87371, GSE31312). RESULTS: Comprehensive genomic analysis of 1,143 DLBCL samples identify 2 molecularly, prognostically relevant subtypes: immune-enriched (IME) and cell-cycle-enriched (CCE). Then a new predictive model including seven key genes (SERPING1, TIMP2, NME1, DCTPP1, RFC4, POLE2, and SNRPD1) was developed with high prediction accuracy (88.6%) and strong predictive power (AUC = 0.973) based on the Support Vector Machine (SVM) algorithm in 414 patients from GSE10846. The predictive power was similar in another three testing sets (HR > 1.400, p < 0.05). CONCLUSION: This model could evaluate survival independently with strong predictive power compared with other clinical risk factors. Our study constructed a reliable model to predict two new subtypes of DLBCL patients, which could guide the implementation of individualized treatment.

The correlation between clinical outcomes and genomic analysis with high risk factors for the progression of osteosarcoma.

Osteosarcoma (OS) is a rare but aggressive malignancy. Despite previous reports, molecular characterization of this disease is not well understood, and little is known regarding OS in Chinese patients. Herein, we analyzed the genomic signatures of 73 Chinese OS cases. TP53, NCOR1, LRP1B, ATRX, RB1, and TFE3 were the most frequently mutated gene in our OS cohort. In addition, the genomic analysis of Western OS patients was performed. Notably, there were remarkable disparities in mutational landscape, base substitution pattern, and tumor mutational burden between the Chinese and Western OS cohorts. Specific molecular mechanisms, including DNA damage repair (DDR) gene mutations, copy number variation (CNV) presence, aneuploidy, and intratumoral heterogeneity, were associated with disease progression. Additionally, 30.1% of OS patients carried clinically actionable alterations, which were mainly enriched in PI3K, MAPK, DDR, and RTK signaling pathways. A specific molecular subtype incorporating DDR alterations and CNVs was significantly correlated with distant metastasis-free survival and event-free survival, and this correlation was observed in all subgroups with different characteristics. These findings comprehensively elucidated the genomic profile and revealed novel prognostic factors in OS, which would contribute to understanding this disease and promoting precision medicine of this population.

The mutational pattern of homologous recombination repair genes in urothelial carcinoma and its correlation with immunotherapeutic response.

BACKGROUND: The mutational pattern of homologous recombination repair (HRR)-associated gene alterations in Chinese urothelial carcinoma (UC) necessitates comprehensive sequencing efforts, and the clinical implications of HRR gene mutations in UC remain to be elucidated. MATERIALS AND METHODS: We delineated the mutational landscape of 343 Chinese UC patients from West China Hospital and 822 patients from The Cancer Genome Atlas (TCGA) using next-generation sequencing (NGS). Data from 182 metastatic UC patients from MSK-IMPACT cohort were used to assess the association between HRR mutations and immunotherapy efficacy. Comprehensive transcriptomic analysis was performed to explore the impact of HRR mutations on tumor immune microenvironment. RESULTS: Among Chinese UC patients, 34% harbored HRR gene mutations, with BRCA2, ATM, BRCA1, CDK12, and RAD51C being the most prevalently mutated genes. Mutational signatures contributing to UC differed between patients with and without HRR mutations. Signature 22 for exposure to aristolochic acid was only observed in Chinese UC patients. The presence of HRR mutations was correlated with higher tumor mutational burden, neoantigen burden, and PD-L1 expression. Importantly, patients with HRR mutations exhibited significantly improved prognosis following immunotherapy compared to those without HRR mutations. CONCLUSIONS: Our findings provide valuable insights into the genomic landscape of Chinese UC patients and underscore the molecular rationale for utilizing immunotherapy in UC patients with HRR mutations.

BCAT2 promotes melanoma progression by activating lipogenesis via the epigenetic regulation of FASN and ACLY expressions.

Melanoma is the most lethal skin cancer originating from the malignant transformation of epidermal melanocyte. The dysregulation of cellular metabolism is a hallmark of cancer, including in melanoma. Aberrant branched-chain amino acids (BCAA) metabolism and related enzymes has been greatly implicated in the progression of multiple types of cancer, whereas remains far from understood in melanoma. Herein, we reported that the critical BCAA metabolism enzyme branched-chain amino acid transaminase 2 (BCAT2) is an oncogenic factor in melanoma by activating lipogenesis via the epigenetic regulation of fatty acid synthase (FASN) and ATP-citrate lyase (ACLY) expressions. Firstly, we found that BCAT2 expression was prominently increased in melanoma, and highly associated with clinical stage. Then, it was proved that the deficiency of BCAT2 led to impaired tumor cell proliferation, invasion and migration in vitro, and tumor growth and metastasis in vivo. Further, RNA sequencing technology and a panel of biochemical assays demonstrated that BCAT2 regulated de novo lipogenesis via the regulation of the expressions of both FASN and ACLY. Mechanistically, the inhibition of BCAT2 suppressed the generation of intracellular acetyl-CoA, mitigating P300-dependent histone acetylation at the promoter of FASN and ACLY, and thereby their transcription. Ultimately, zinc finger E-box binding homeobox 1 (ZEB1) was identified as the upstream transcriptional factor responsible for BCAT2 up-regulation in melanoma. Our results demonstrate that BCAT2 promotes melanoma progression by epigenetically regulating FASN and ACLY expressions via P300-dependent histone acetylation. Targeting BCAT2 could be exploited as a promising strategy to restrain tumor progression in melanoma.

Construction of a Dual-Emissive Probe for Discriminative Visualization of Lysosomal and Mitochondrial Dysfunction.

Discriminatively visualizing mitochondrial and lysosomal dysfunction is crucial for an in-depth understanding of cell apoptosis regulation and relative biology. However, fluorescent probes for the separate visualization of lysosomal and mitochondria damages have not been reported yet. Herein, we have constructed a fluorescent probe [2-(4-hydroxystyryl)-1,3,3-trimethyl-3H-indol-1-ium iodide (HBSI)] for labeling mitochondria and lysosomes in dual emission colors and discriminatively imaging mitochondrial and lysosomal damage in two different sets of fluorescent signals. In living cells, HBSI targeted both lysosomes and mitochondria to give green and red emission, respectively. During mitochondrial damages, HBSI immigrated into lysosomes, and the red emission decreased. During lysosomal damage, HBSI immigrated into mitochondria, and the green emission decreased. With the robust probe, the different damaging sequences of mitochondria and lysosomes under different amounts of H2O2 and chloral hydrate have been revealed. The sequential damage of lysosomes and mitochondria during cell apoptosis induced by rotenone, paclitaxel, and colchicine has been discovered. Furthermore, the regulation of mitochondria, lysosome, and their interplay during autophagy was also observed with the probe.

Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer.

Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

Mutational pattern off homologous recombination repair (HRR)-related genes in upper tract urothelial carcinoma.

BACKGROUND: Homologous recombination (HR) repair (HRR) has been indicated to be a biomarker for immunotherapy, chemotherapy, and poly-ADP ribose polymerase inhibitors inhibitors (PARPis). Nonetheless, their molecular correlates in upper tract urothelial carcinoma (UTUC) have not been well studied. This study aimed to explore the molecular mechanism and tumor immune profile of HRR genes and the relevance of their prognostic value in patients with UTUC. MATERIALS AND METHODS: One hundred and ninety-seven tumors and matched blood samples from Chinese UTUC were subjected to next-generation sequencing. A total of 186 patients from The Cancer Genome Atlas were included. Comprehensive analysis was performed. RESULTS: In Chinese patients with UTUC, 5.01% harbored germline HRR gene mutations, and 1.01% had Lynch syndrome-related genes. A total of 37.6% (74/197) of patients carried somatic or germline HRR gene mutations. There was marked discrepancy in the mutation landscapes, genetic interactions, and driver genes between the HRR-mut cohorts and HRR-wt cohorts. Aristolochic acid signatures and defective DNA mismatch repair signatures only existed in individuals in the HRR-mut cohorts. Inversely, the unknown signature (signature A) and signature SBS55 only existed in patients in the HRR-wt cohorts. HRR gene mutations regulated immune activities by NKT cells, plasmacytoid dendritic cells, hematopoietic stem cell, and M1 macrophages. In patients with local recurrence, patients with HRR gene mutations had poorer DFS rates than patients with wild-type HRR genes. CONCLUSIONS: Our results imply that the detection of HRR gene mutations can predict recurrence in patients with UC. In addition, this study provides a path to explore the role of HRR-directed therapies, including PARPis, chemotherapy, and immunotherapy.