The current World Health Organization (WHO) classification of nasopharyngeal carcinoma (NPC) conveys little prognostic information. This study aimed to propose an NPC histopathologic classification that can potentially be used to predict prognosis and treatment response.We initially developed a histopathologic classification based on the morphologic traits and cell differentiation of tumors of 2716 NPC patients who were identified at Sun Yat-sen University Cancer Center (SYSUCC) (training cohort). Then, the proposed classification was applied to 1702 patients (retrospective validation cohort) from hospitals outside SYSUCC and 1613 patients (prospective validation cohort) from SYSUCC. The efficacy of radiochemotherapy and radiotherapy modalities was compared between the proposed subtypes. We used Cox proportional hazards models to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS).The 5-year OS rates for all NPC patients who were diagnosed with epithelial carcinoma (EC; 3708 patients), mixed sarcomatoid-epithelial carcinoma (MSEC; 1247 patients), sarcomatoid carcinoma (SC; 823 patients), and squamous cell carcinoma (SCC; 253 patients) were 79.4%, 70.5%, 59.6%, and 42.6%, respectively (P < 0.001). In multivariate models, patients with MSEC had a shorter OS than patients with EC (HR = 1.44, 95% CI = 1.27-1.62), SC (HR = 2.00, 95% CI = 1.76-2.28), or SCC (HR = 4.23, 95% CI = 3.34-5.38). Radiochemotherapy significantly improved survival compared with radiotherapy alone for patients with EC (HR = 0.67, 95% CI = 0.56-0.80), MSEC (HR = 0.58, 95% CI = 0.49-0.75), and possibly for those with SCC (HR = 0.63; 95% CI = 0.40-0.98), but not for patients with SC (HR = 0.97, 95% CI = 0.74-1.28).The proposed classification offers more information for the prediction of NPC prognosis compared with the WHO classification and might be a valuable tool to guide treatment decisions for subtypes that are associated with a poor prognosis.
Lymph node status is the primary determinant in treatment decision making in early gastric cancer (EGC). Current evaluation methods are not adequate for estimating lymph node metastasis (LNM) in EGC.To develop and validate a prediction model based on a fully quantitative collagen signature in the tumor microenvironment to estimate the individual risk of LNM in EGC.This retrospective study was conducted from August 1, 2016, to May 10, 2018, at 2 medical centers in China (Nanfang Hospital and Fujian Provincial Hospital). Participants included a primary cohort (n = 232) of consecutive patients with histologically confirmed gastric cancer who underwent radical gastrectomy and received a T1 gastric cancer diagnosis from January 1, 2008, to December 31, 2012. Patients with neoadjuvant radiotherapy, chemotherapy, or chemoradiotherapy were excluded. An additional consecutive cohort (n = 143) who received the same diagnosis from January 1, 2011, to December 31, 2013, was enrolled to provide validation. Baseline clinicopathologic data of each patient were collected. Collagen features were extracted in specimens using multiphoton imaging, and the collagen signature was constructed. An LNM prediction model based on the collagen signature was developed and was internally and externally validated.The area under the receiver operating characteristic curve (AUROC) of the prediction model and decision curve were analyzed for estimating LNM.In total, 375 patients were included. The primary cohort comprised 232 consecutive patients, in whom the LNM rate was 16.4% (n = 38; 25 men [65.8%] with a mean [SD] age of 57.82 [10.17] years). The validation cohort consisted of 143 consecutive patients, in whom the LNM rate was 20.9% (n = 30; 20 men [66.7%] with a mean [SD] age of 54.10 [13.19] years). The collagen signature was statistically significantly associated with LNM (odds ratio, 5.470; 95% CI, 3.315-9.026; P < .001). Multivariate analysis revealed that the depth of tumor invasion, tumor differentiation, and the collagen signature were independent predictors of LNM. These 3 predictors were incorporated into the new prediction model, and a nomogram was established. The model showed good discrimination in the primary cohort (AUROC, 0.955; 95% CI, 0.919-0.991) and validation cohort (AUROC, 0.938; 95% CI, 0.897-0.981). An optimal cutoff value was selected in the primary cohort, which had a sensitivity of 86.8%, a specificity of 93.3%, an accuracy of 92.2%, a positive predictive value of 71.7%, and a negative predictive value of 97.3%. The validation cohort had a sensitivity of 90.0%, a specificity of 90.3%, an accuracy of 90.2%, a positive predictive value of 71.1%, and a negative predictive value of 97.1%. Among the 375 patients, a sensitivity of 87.3%, a specificity of 92.1%, an accuracy of 91.2%, a positive predictive value of 72.1%, and a negative predictive value of 96.9% were found.This study's findings suggest that the collagen signature in the tumor microenvironment is an independent indicator of LNM in EGC, and the prediction model based on this collagen signature may be useful in treatment decision making for patients with EGC.
Abstract Background Gastric cancer is a highly heterogeneous disease, presenting a major obstacle to personalized treatment. Effective markers of the immune checkpoint blockade response are needed for precise patient classification. We, therefore, divided patients with gastric cancer according to collagen gene expression to indicate their prognosis and treatment response. Methods We collected data for 1250 patients with gastric cancer from four cohorts. For the TCGA‐STAD cohort, we used consensus clustering to stratify patients based on expression levels of 44 collagen genes and compared the prognosis and clinical characteristics between collagen subtypes. We then identified distinct transcriptomic and genetic alteration signatures for the subtypes. We analyzed the associations of collagen subtypes with the responses to chemotherapy, immunotherapy, and targeted therapy. We also established a platform‐independent collagen‐subtype predictor. We verified the findings in three validation cohorts (GSE84433, GSE62254, and GSE15459) and compared the collagen subtyping method with other molecular subtyping methods. Results We identified two subtypes of gastric adenocarcinoma: a high‐expression collagen subtype (CS‐H) and a low‐expression collagen subtype (CS‐L). Collagen subtype was an independent prognostic factor, with better overall survival in the CS‐L subgroup. The inflammatory response, angiogenesis, and phosphoinositide 3‐kinase (PI3K)/Akt pathways were transcriptionally active in the CS‐H subtype, while DNA repair activity was significantly greater in the CS‐L subtype. PIK3CA was frequently amplified in the CS‐H subtype, while PIK3C2A , PIK3C2G , and PIK3R1 were frequently deleted in the CS‐L subtype. CS‐H subtype tumors were more sensitive to fluorouracil, while CS‐L subtype tumors were more sensitive to immune checkpoint blockade. CS‐L subtype was predicted to be more sensitive to HER2‐targeted drugs, and CS‐H subtype was predicted to be more sensitive to vascular endothelial growth factor and PI3K pathway‐targeting drugs. Collagen subtyping also has the potential to be combined with existing molecular subtyping methods for better patient classification. Conclusions We classified gastric cancers into two subtypes based on collagen gene expression and validated these subtypes in three validation cohorts. The collagen subgroups differed in terms of prognosis, clinical characteristics, transcriptome, and genetic alterations. The subtypes were closely related to patient responses to chemotherapy, immunotherapy, and targeted therapy.
Epstein-Barr virus (EBV)-positive diffuse large B-cell lymphoma (EBV+ DLBCL) is typically an aggressive tumor in elderly patients. However, in a subset of young patients, EBV+ DLBCL follows a relatively indolent clinical course and exhibits a good response to chemotherapy. This lymphoma comprises polymorphous lymphoma and large cell lymphomas subtypes, with the latter subtype showing a significantly poorer prognosis. It is unknown whether the genetic background differs between age groups and histopathological subtypes. To investigate the genetic basis, heterogeneity, and recurrently mutated genes in EBV+ DLBCL, we performed whole-exome sequencing of DNA from 11 tissue samples of this lymphoma. Sequencing revealed that the most common substitution was the transition C>T/G>A. Genetic features—including the numbers of mutated genes in exonic region, single-nucleotide variants (SNV), and indels—did not significantly differ between age groups or histological subtypes. Matching with the COSMIC database revealed that the main mutational signature was signature 3, which is associated with failure of DNA double-strand break-repair by homologous recombination. Mutant-Allele Tumor Heterogeneity (MATH) scores showed that EBV+ DLBCL exhibited broad intratumor heterogeneity, and were positively correlated with Ann Arbor Stage and ≥2 extranodal lesion sites. We identified 57 selected recurrently mutated genes. The most commonly mutated five genes—LNP1 (11/11), PRSS3 (10/11), MUC3A (9/11), FADS6 (9/11), and TRAK1 (8/11)—were validated by Sanger sequencing. These mutated genes have not previously been identified. Overall, our present results demonstrate the tremendous genetic heterogeneity underlying EBV+ DLBCLs, and highlight the need for personalized therapeutic approaches to treating these patients.
Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in China. Most HCC patients have the complications of chronic liver disease and need overall consideration and whole-course management, including diagnosis, treatment, and follow-up. To develop a reasonable, long-term, and complete management plan, multiple factors need to be considered, including the patient’s general condition, basic liver diseases, tumor stage, tumor biological characteristics, treatment requirements, and economic cost. Summary: To better guide the whole-course management of HCC patients, the Chinese Association of Liver Cancer and the Chinese Medical Doctor Association has gathered multidisciplinary experts and scholars in relevant fields to formulate the “Chinese Expert Consensus on The Whole-Course Management of Hepatocellular Carcinoma (2023).” Key Messages: This expert consensus, based on the current clinical evidence and experience, proposes surgical and nonsurgical HCC management pathways and involves 18 recommendations, including perioperative treatment, systematic treatment combined with local treatment, conversion treatment, special population management, symptomatic support treatment, and follow-up management.
Currently, hematoxylin-eosin (H-E) stained histopathology is the golden standard for diagnosing lung cancer. This time-consuming procedure needs tissue biopsy, sample fixation, slicing, and labeling. Therefore, the availability of a noninvasive optical diagnosis that can obtain real-time analysis comparable to golden standard H-E stained histopathology will be of extraordinary benefit to the medical community. In this study, we investigated whether multiphoton imaging can make real-time optical diagnosis for normal and cancerous lung tissue, compared with H-E stained histopathology. In the normal lung tissue, we found that multiphoton imaging could display normal lung parenchyma composed of alveolar spaces separated by thin septa. In the cancerous lung tissue, multiphoton imaging clearly illustrated that cancer cells displayed marked cellular and nuclear pleomorphism. These cancer cells were characterized by irregular size and shape, enlarged nuclei, and increased nuclear-cytoplasmic ratio. All of these histopathological features of tissue architecture and cell morphology identified by multiphoton images were readily correlated with H-E staining images. All together, multiphoton imaging can make real-time optical diagnosis for lung cancer. This study provides the groundwork for further using multiphoton imaging to perform real-time noninvasive "optical biopsy" for lung cancer in the near future.
Galectin-3 serves an important function in cancer development and progression. The present study aimed to explore the association between single nucleotide polymorphisms in galectin-3, and the susceptibility to chemotherapy drug resistance of gastric carcinoma. The present study was a case-control study including 479 patients with gastric carcinoma and 458 cancer-free controls in a population from the Fujian province in Southeast China. Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry was used to determine the genotype of rs4644 and rs4652, and immunohistochemistry was used to identify the expression level of various proteins associated with chemotherapeutic drug resistance. The results revealed that individuals exhibiting the rs4652 CA/AA genotype had a significantly increased risk of developing gastric carcinoma compared with the rs4652 CC genotype (adjusted odds ratio, 1.51; 95% confidence interval, 1.05-2.18; adjusted P=0.03). In addition, it was demonstrated that there were significant differences in the P-glycoprotein expression level depending on rs4652 genotypic distributions (χ2=9.063; P=0.028). Therefore, the present study demonstrated that rs4652 single nucleotide polymorphisms of the galectin-3 gene contribute to the susceptibility to and chemotherapeutic drug resistance of gastric carcinoma.
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