SLC7A11 promotes EMT and metastasis in invasive pituitary neuroendocrine tumors by activating the PI3K/AKT signaling pathway.

Invasive pituitary neuroendocrine tumors (PitNETs) are the most prevalent types of intracranial and neuroendocrine tumors. Their aggressive growth and difficulty in complete resection result in a high recurrence rate. Cystine transporter solute carrier family 7 member 11 (SLC7A11) is overexpressed in various cancers, which contributes to tumor growth, progression, and metastasis by promoting cystine uptake and glutathione biosynthesis. We identified SLC7A11 as an invasive biomarker based on three Gene Expression Omnibus cohorts. This study aimed to investigate the role of SLC7A11 in invasive PitNETs. Cell proliferation was assessed using CCK-8 and colony formation assays, while cell apoptosis was estimated with flow cytometry. Wound healing assays and transwell assays were utilized to evaluate migration and invasion ability. Our findings demonstrated that SLC7A11 was markedly upregulated in invasive PitNETs, and was associated with the invasiveness of PitNETs. Knockdown of SLC7A11 could largely suppress tumor cell proliferation, migration, and invasion, while inducing apoptosis. Furthermore, SLC7A11 depletion was implicated in regulating epithelial-mesenchymal transition and inactivating the PI3K/AKT signaling pathway. These insights suggest SLC7A11 as a potential therapeutic target for invasive PitNETs.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study.

Background: Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Methods: Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. Results: An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. Conclusions: This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

Comprehensive analyses of m1A regulator-mediated modification patterns determining prognosis in lower-grade glioma (running title: m1A in LGG).

N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.

Correction: Mechanisms of the ethanol extract of Gelidium amansii for slow aging in high-fat male Drosophila by metabolomic analysis.

Correction for 'Mechanisms of the ethanol extract of Gelidium amansii for slow aging in high-fat male Drosophila by metabolomic analysis' by Yushi Chen et al., Food Funct., 2022, 13, 10110-10120, https://doi.org/10.1039/D2FO02116A.

Total Neoadjuvant Therapy With PD-1 Blockade for High-Risk Proficient Mismatch Repair Rectal Cancer.

Importance: Total neoadjuvant therapy (TNT) is the standard treatment for locally advanced rectal cancer, especially for patients with high-risk factors. However, the efficacy of TNT combined with immunotherapy for patients with proficient mismatch repair (pMMR) rectal cancer is unknown. Objectives: To evaluate the safety and efficacy of TNT with induction chemoimmunotherapy followed by long-course chemoradiation in patients with high-risk, pMMR rectal cancer and to identify potential molecular biomarkers associated with treatment efficacy. Design, Setting, and Participants: This cohort study was a single-arm phase 2 trial conducted at Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, from June 2020 to October 2021. Biopsies and plasma were collected before treatment for whole-exome sequencing and cell-free DNA sequencing, respectively. Data were analyzed from May 2022 to September 2022. Interventions: Participants received 3 cycles of induction oxaliplatin and capecitabine combined with camrelizumab and radiotherapy (50.6 Gy in 22 fractions) with concurrent capecitabine. Patients without disease progression received 2 cycles of consolidation oxaliplatin/capecitabine. Main Outcomes and Measures: The primary end point was pathologic complete response rate. Results: Of 25 patients enrolled (19 men [76%]; 6 women [24%]; median [IQR] age, 58 [48-64] years), 22 patients (88%) completed the TNT schedule. The pathologic complete response rate was 33.3% (7/21). Twelve patients (48%) achieved clinical complete response, and 4 patients (16%) chose to watch and wait. R0 resection was achieved in 21 of 21 patients, and the major pathologic response rate was 38.1% (8/21). The most common adverse event was nausea (80%, 20/25); grade 3 toxic effects occurred in 9 of 25 patients (36%). Patients with tumor shrinkage of 50% or greater after induction oxaliplatin/capecitabine and camrelizumab or clinical complete response had higher percentages of LRP1B mutation. Mutation of LRP1B was associated with high tumor mutation burden and tumor neoantigen burden. Patients with high tumor mutation burden all benefited from therapy. Conclusions and Relevance: This study found that TNT with induction chemoimmunotherapy followed by long-course chemoradiation was safe and effective for patients with high-risk rectal cancer with pMMR status. Longer follow-up and larger clinical studies are needed to validate this innovative regimen. There is also an urgent need to further validate the predictive value of LRP1B and discover other novel biomarkers with potential predictive value for rectal cancer.

Investigation of cuproptosis regulator-mediated modification patterns and SLC30A7 function in GBM.

BACKGROUND: Copper-dependent controlled cell death (cuproptosis) is a novel cell death modality that is distinct from known cell death mechanisms. Nonetheless, the potential role of the cuproptosis regulator in tumour microenvironment (TME) of GBM remains unknown. METHODS: Based on 13 widely recognised cuproptosis regulators, the cuproptosis regulation patterns and the biological characteristics of each pattern were comprehensively assessed in GBMs. Machine learning strategies were used to construct a CupScore to quantify the cuproptosis regulation patterns of individual tumours. A PPI network was constructed to predict core-associated genes of cuproptosis regulators. The function of the novel cuproptosis regulators SLC30A7 was examined by in vitro and in vivo experiment. RESULTS: We identified three distinct cuproptosis regulation patterns, including immune activation, metabolic activation, and immunometabolic double deletion patterns. The CupScore was shown to predict the abundance of tumour inflammation, molecular subtype, stromal activity, gene variation, signalling pathways, and patient prognosis. The low CupScore subtype was characterised by immune activation, isocitrate dehydrogenase mutations, sensitivity to chemotherapy, and clinical benefits. The high CupScore subtype was characterised by activation of the stroma and metabolism and poor survival. Novel cuproptosis regulator SLC30A7 knockdown inhibited the cuproptosi via JAK2/STAT3/ATP7A pathway in GBM. CONCLUSION: Cuproptosis regulators have been shown to play a vital role in TME complexity. Constructing CupScores were trained to evaluate the regulation patterns of cuproptosis in individual tumours. The novel cuproptosis-related genes SLC30A7 was involved in regulation the tumorigenicity of GBM cell via JAK2/STAT3/ATP7A pathway in vitro and in vivo.

An Adaptive Deconvolution Method with Improve Enhanced Envelope Spectrum and Its Application for Bearing Fault Feature Extraction.

To address the problem that complex bearing faults are coupled to each other, and the difficulty of diagnosis increases, an improved envelope spectrum-maximum second-order cyclostationary blind deconvolution (IES-CYCBD) method is proposed to realize the separation of vibration signal fault features. The improved envelope spectrum (IES) is obtained by integrating the part of the frequency axis containing resonance bands in the cyclic spectral coherence function. The resonant bands corresponding to different fault types are accurately located, and the IES with more prominent target characteristic frequency components are separated. Then, a simulation is carried out to prove the ability of this method, which can accurately separate and diagnose fault types under high noise and compound fault conditions. Finally, a compound bearing fault experiment with inner and outer ring faults is designed, and the inner and outer ring fault characteristics are successfully separated by the proposed IES-CYCBD method. Therefore, simulation and experiments demonstrate the strong capability of the proposed method for complex fault separation and diagnosis.

A benchmarking framework for the accurate and cost-effective detection of clinically-relevant structural variants for cancer target identification and diagnosis.

BACKGROUND: Accurate clinical structural variant (SV) calling is essential for cancer target identification and diagnosis but has been historically challenging due to the lack of ground truth for clinical specimens. Meanwhile, reduced clinical-testing cost is the key to the widespread clinical utility. METHODS: We analyzed massive data from tumor samples of 476 patients and developed a computational framework for accurate and cost-effective detection of clinically-relevant SVs. In addition, standard materials and classical experiments including immunohistochemistry and/or fluorescence in situ hybridization were used to validate the developed computational framework. RESULTS: We systematically evaluated the common algorithms for SV detection and established an expert-reviewed SV call set of 1,303 tumor-specific SVs with high-evidence levels. Moreover, we developed a random-forest-based decision model to improve the true positive of SVs. To independently validate the tailored 'two-step' strategy, we utilized standard materials and classical experiments. The accuracy of the model was over 90% (92-99.78%) for all types of data. CONCLUSION: Our study provides a valuable resource and an actionable guide to improve cancer-specific SV detection accuracy and clinical applicability.

Multi-omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma.

BACKGROUND: Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ). METHODS: Primary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed. RESULTS: WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion. CONCLUSIONS: This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.

Simulation and experimental study on the stability and comfortability of the wheelchair human system under uneven pavement.

With the improvement in the level of science and technology and the improvement of people's living standards, the functions of traditional manual wheelchairs have been unable to meet people's living needs. Therefore, traditional wheelchairs have been gradually replaced by smart wheelchairs. Compared with traditional wheelchairs, smart wheelchairs have the characteristics of light operation and faster speed. However, when driving on some complex road surfaces, the vibration generated by the bumps of the motorcycle will cause damage to the human body, so wheelchairs with good electric power and stability can better meet the needs of people and make up for their travel needs. Based on the traditional vehicle stability analysis method, the mathematical theory of roll stability and pitch stability of the wheelchair-human system was established. We built a multi-body dynamics model with human skeleton and joint stiffness based on the multi-body dynamics method. The functioning of the wheelchair-human system was simulated and analyzed on the ditch, step, and combined road. The acceleration and Euler angle changes of the human head, chest, and wheelchair truss position were obtained, and the data results were analyzed to evaluate the stability and comfort of the system. Finally, a wheelchair test platform was built, and the road driving test was carried out according to the simulation conditions to obtain the system acceleration and angle data during the driving process. The simulation analysis was compared to verify the accuracy of the multi-body dynamics method, and the stability and comfort of the system were evaluated.

Characterization of the tumor microenvironment and identification of spatially predictive biomarkers associated with beneficial neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Neoadjuvant chemoradiotherapy (nCRT) has become the standard treatment for patients with locally advanced rectal cancer (LARC). However, 20-40% of patients with LARC show little to no response to nCRT. Thus, comprehensively understanding the tumor microenvironment (TME), which might influence therapeutic efficacy, and identifying robust predictive biomarkers is urgently needed. Pre-treatment tumor biopsy specimens from patients with LARC were evaluated in detail through digital spatial profiling (DSP), public RNA sequencing datasets, and multiplex immunofluorescence (mIF). DSP analysis revealed distinct characteristics of the tumor stroma compared to the normal stroma and tumor compartments. We identified high levels of human leukocyte antigen-DR/major histocompatibility complex class II (HLA-DR/MHC-II) in the tumor compartment and B cells in the stroma as potential spatial predictors of nCRT efficacy in the Discovery cohort. Public datasets validated their predictive capacity for clinical outcomes. Using mIF in an independent nCRT cohort and/or the total cohort, we validated that a high density of HLA-DR/MHC-II+ cells in the tumor and CD20 + B cells in the stroma was associated with nCRT efficacy (all p ≤ 0.021). Spatial profiling successfully characterized the LARC TME and identified robust biomarkers with the potential to accurately predict nCRT response. These findings have important implications for individualized therapy.

The HNF4A-CHPF pathway promotes proliferation and invasion through interactions with MAD1L1 in glioma.

Chondroitin polymerizing factor (CHPF) is an important glycosyltransferases that participates in the biosynthesis of chondroitin sulfate (CS). Our previous study showed that silencing CHPF expression inhibited glioma cell proliferation in vitro, but the molecular mechanisms by which CHPF contributes to development of glioma have not been characterized. In this study, we found that CHPF was up-regulated in glioma tissues and was positively correlated with malignant clinical pathological characteristics of patients with glioma. Silencing CHPF expression inhibited proliferation, colony formation, migration, and cell cycle of glioma cells. Moreover, silencing CHPF suppressed glioma malignance in vivo. Immunoprecipitation, co-immunoprecipitation, GST pulldown, and liquid chromatography-mass spectrometry (LC-MS/MS) assays were used to verify the interaction between CHPF and Mitotic arrest deficient 1-like 1 (MAD1L1). In addition, Chromatin Immunoprecipitation (ChIP)-PCR analysis showed that HNF4A bound to the CHPF promoter region, which indicated that the transcription factor hepatocyte nuclear factor 4A (HNF4A) could regulate the expression of CHPF in glioma cells.

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research.

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

Proteomic Profiling and Tumor Microenvironment Characterization Reveal Molecular and Immunological Hallmarks of Left-Sided and Right-Sided Colon Cancer Tumorigenesis.

Left-sided and right-sided colon cancer (LSCC and RSCC) display different biological and clinical characteristics. However, the differences in their tumorigenesis and tumor microenvironment remain unclear. In this study, we profiled the proteomic landscapes of LSCC and RSCC with data-independent acquisition mass spectrometry (DIA-MS) using fresh tumor and adjacent normal tissues from 24 patients. A total of 7403 proteingroups were primarily identified with DIA-MS. After quality control, 7212 proteingroups were used for further analysis. Through comparing the difference in proteomic profiles between LSCC and RSCC samples, 2556 commonly and 1982 region-type-specific regulated proteingroups were characterized. During the development of LSCC and RSCC, metabolic, growth, cell division, cell adhesion, and migration pathways were found to be significantly dysregulated (P < 0.05), which was further confirmed by transcriptome data from TCGA. Compared to RSCC, most parts of the immune-related signatures, immune cell infiltration scores, and overall immune scores of LSCC were higher. The systematic elucidation of proteomic and transcriptomic profiles in this work improves our understanding of tumorigenesis and immune microenvironment characteristics of LSCC and RSCC.

Primary pituitary stalk mucosa-associated lymphoid tissue lymphoma: a case report and literature review.

Background: Primary extranodal mucosa-associated lymphoid tissue (MALT) lymphoma in the sellar region is a rare indolent B-cell lymphoma. Case presentation: A newly diagnosed patient with MALT lymphoma originating from the pituitary stalk is reported. A space-occupying lesion in the sellar region was found in a 24 year-old man who had no clinical symptoms except for those relating to a sex hormone disorder (rising estrogen and falling androgen) identified during a pre-employment physical examination. MALT lymphoma was diagnosed pathologically. Radiotherapy and chemotherapy were proposed after surgery. However, the patient selected androgen replacement therapy only rather than chemoradiotherapy. Over the next 3 months, no visual disturbance, headache, cranial nerve abnormality, or other symptoms occurred. Conclusion: Primary sellar region MALT lymphoma is an extremely rare disease. The differential diagnosis of sellar and parasellar masses should include primary sellar region MALT lymphoma. Early detection and treatment of this lymphoma can effectively improve the prognosis.

Mining glycosylation-related prognostic lncRNAs and constructing a prognostic model for overall survival prediction in glioma: A study based on bioinformatics analysis.

Dysregulation of protein glycosylation plays a crucial role in the development of glioma. Long noncoding RNA (lncRNAs), functional RNA molecules without protein-coding ability, regulate gene expression and participate in malignant glioma progression. However, it remains unclear how lncRNAs are involved in glycosylation glioma malignancy. Identification of prognostic glycosylation-related lncRNAs in gliomas is necessary. We collected RNA-seq data and clinicopathological information of glioma patients from the cancer genome atlas and Chinese glioma genome atlas. We used the "limma" package to explore glycosylation-related gene and screened related lncRNAs from abnormally glycosylated genes. Using univariate Cox analyses Regression and least absolute shrinkage and selection operator analyses, we constructed a risk signature with 7 glycosylation-related lncRNAs. Based on the median risk score (RS), patients with gliomas were divided into low- and high-risk subgroups with different overall survival rates. Univariate and multivariate Cox analyses regression analyses were performed to assess the independent prognostic ability of the RS. Twenty glycosylation-related lncRNAs were identified by univariate Cox regression analyses. Two glioma subgroups were identified using consistent protein clustering, with the prognosis of the former being better than that of the latter. Least absolute shrinkage and selection operator analysis identified 7 survival RSs for glycosylation-related lncRNAs, which were identified as independent prognostic markers and predictors of glioma clinicopathological features. Glycosylation-related lncRNAs play an important role in the malignant development of gliomas and may help guide treatment options.

Single-cell analyses reveal distinct expression patterns and roles of long non-coding RNAs during hESC differentiation into pancreatic progenitors.

BACKGROUND: Deep understanding the differentiation process of human embryonic stem cells (hESCs) is essential for developing cell-based therapeutic strategy. Substantial efforts have been made to investigate protein-coding genes, yet it remains lacking comprehensive characterization of long non-coding RNAs (lncRNAs) during this process. METHODS: hESCs were passaged every 5-6 days and had maintained stable karyotype even until the 50th generation. Pancreatic progenitor specification of in vitro differentiation from hESCs was performed and modified. The nuclei were stained with 4,6-Diamidino-2-phenylindole (DAPI). Droplet-based platform (10X Genomics) was applied to generate the single-cell RNA sequencing (scRNA-seq) data. The quality of the filtered read pairs was evaluated by using FastQC. Batch effects were removed using the size factor method. Dimension reduction and unsupervised clustering analyses were performed using Seurat R package. The Monocle 2 and MetaCell algorithms were used to order single cells on a pseudotime course and partition the scRNA-seq data into metacells, respectively. Co-expression network was constructed using WGCNA. Module- and hub-based methods were adopted to predict the functions of lncRNAs. RESULTS: A total of 77,382 cells during the differentiation process of hESCs toward pancreatic progenitors were sequenced. According to the single-cell map, the cells from different time points were authenticated to constitute a relatively homogeneous population, in which a total of 7382 lncRNAs could be detected. Through further analyzing the time course data, conserved and specific expression features of lncRNAs during hESC differentiation were revealed. Based upon pseudotime analysis, 52 pseudotime-associated lncRNAs that grouped into three distinct expression patterns were identified. We also implemented MetaCell algorithm and network-based methods to explore the functional mechanisms of these lncRNAs. Totally, 464 lncRNAs, including 49 pseudotime-associated lncRNAs were functionally annotated by either module-based or hub-based methods. Most importantly, we demonstrated that the lncRNA HOTAIRM1, which co-localized and co-expressed with several HOX genes, may play crucial role in the generation of pancreatic progenitors through regulation of exocytosis and retinoic acid receptor signaling pathway. CONCLUSIONS: Our single-cell analyses provide valuable data resources for biological researchers and novel insights into hESC differentiation processes, which will guide future endeavors to further elucidate the roles of lncRNAs.

Multi-omics analysis uncovers tumor ecosystem dynamics during neoadjuvant toripalimab plus nab-paclitaxel and S-1 for esophageal squamous cell carcinoma: a single-center, open-label, single-arm phase 2 trial.

BACKGROUND: Immune checkpoint inhibitors combined with chemotherapy as a neoadjuvant therapy have been applied to the treatment of esophageal squamous cell carcinoma (ESCC). However, the optimal regimen needs to be further explored, particularly for older patients, and the mechanisms by which the immune checkpoint inhibitor combined with chemotherapy modulates the evolution of ESCC are unknown. METHODS: In this single-arm phase 2 trial, patients with resectable (stage II/III/IV without metastasis) ESCC were enrolled and received nanoparticle albumin-bound (nab) paclitaxel for two cycles and oral S-1 for 2 weeks, combined with intravenous toripalimab for two cycles before surgery. Combination postoperative adjuvant therapy was administered. The primary outcome was the major pathological response (MPR). Secondary outcomes included pathological complete response (pCR), overall response rate (ORR), disease control rate (DCR), disease-free survival (DFS), overall survival (OS), improvement in Stooler's dysphagia score and degree of daily living ability (dADL). Biopsies and plasma pre- and post-neoadjuvant therapy were performed using whole-exome sequencing, transcriptome sequencing, immunohistochemistry (IHC) for PD-L1, multiplex immunofluorescence (mIF) and proximity extension assay technology (PEA) for 92 proteins. FINDINGS: From November 2019 to July 2021, 60 patients were enrolled. After neoadjuvant therapy, R0 resection was achieved in 55 (98.21%) patients. MPR was identified in 27 patients (49.09%), and 16 patients (29.09%) achieved pCR. Patients with PR, SD and PD were 37 (61.67%), 21 (35.00%) and 2 (3.33%), respectively. The overall staging, Stooler dysphagia scores and dADL were significantly decreased after treatment. 11 patients (18.3%) experienced grade ≥3 AEs. Compared to PD-L1-Low patients, PD-L1-High patients had a significantly higher ratio of PR. During therapy, the tumor mutation burden (TMB) and tumor neoantigen burden (TNB) were significantly decreased in patients with PR. Differential clonal evolution within tumors was demonstrated by analysis of intratumoral heterogeneity. Transcriptome analyses revealed that the infiltration of CD4+ T lymphocytes at baseline was associated with clinical outcome. During therapy, CD8+ T cells and CD4+ T cells were increased in all patients; however, exhausted cells, nTregs and iTregs were significantly increased in patients with non-MPR. Protein analyses revealed that the levels of IFN-γ, Gal.1 and LAMP3 can predict the clinical benefit. In addition, the expression of CD83, TNFRSF4, TNFSF14, VEGFR2, ADA, ARG1, and HO-1 was associated with serious AEs. More importantly, the integration of CD4+ T cells with plasma protein of IFN-γ, Gal.1 or LAMP3 could further distinguish responders from non-responders. INTERPRETATION: In this study, neoadjuvant therapy with toripalimab, nab-paclitaxel and S-1 was less toxic and showed promising antitumor activity in patients with resectable ESCC. Changes in the genome, transcriptome, PD-L1 expression and serum proteins were comprehensively analyzed and correlated with clinical outcomes, which provides insight into the mechanism of action of toripalimab combined with nab-paclitaxel and S-1 in patients with ESCC. FUNDING: This study was funded by Major projects of the ministry of science and technology of the 13th five-year plan of China [grant number: 2018ZX09201013].

Spatial multi-omics revealed the impact of tumor ecosystem heterogeneity on immunotherapy efficacy in patients with advanced non-small cell lung cancer treated with bispecific antibody.

BACKGROUND: Immunotherapy for malignant tumors has made great progress, but many patients do not benefit from it. The complex intratumoral heterogeneity (ITH) hindered the in-depth exploration of immunotherapy. Conventional bulk sequencing has masked intratumor complexity, preventing a more detailed discovery of the impact of ITH on treatment efficacy. Hence, we initiated this study to explore ITH at the multi-omics spatial level and to seek prognostic biomarkers of immunotherapy efficacy considering the presence of ITH. METHODS: Using the segmentation strategy of digital spatial profiling (DSP), we obtained differential information on tumor and stromal regions at the proteomic and transcriptomic levels. Based on the consideration of ITH, signatures constructed by candidate proteins in different regions were used to predict the efficacy of immunotherapy. RESULTS: Eighteen patients treated with a bispecific antibody (bsAb)-KN046 were enrolled in this study. The tumor and stromal areas of the same samples exhibited distinct features. Signatures consisting of 11 and 18 differentially expressed DSP markers from the tumor and stromal areas, respectively, were associated with treatment response. Furthermore, the spatially resolved signature identified from the stromal areas showed greater predictive power for bsAb immunotherapy response (area under the curve=0.838). Subsequently, our stromal signature was validated in an independent cohort of patients with non-small cell lung cancer undergoing immunotherapy. CONCLUSION: We deciphered ITH at the spatial level and demonstrated for the first time that genetic information in the stromal region can better predict the efficacy of bsAb treatment. TRIAL REGISTRATION NUMBER: NCT03838848.