A predictive radiotranscriptomics model based on DCE-MRI for tumor immune landscape and immunotherapy in cholangiocarcinoma.

This study aims to determine the predictive role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived radiomic model in tumor immune profiling and immunotherapy for cholangiocarcinoma. To perform radiomic analysis, immune related subgroup clustering was first performed by single sample gene set enrichment analysis (ssGSEA). Second, a total of 806 radiomic features for each phase of DCE-MRI were extracted by utilizing the Python package Pyradiomics. Then, a predictive radiomic signature model was constructed after a three-step features reduction and selection, and receiver operating characteristic (ROC) curve was employed to evaluate the performance of this model. In the end, an independent testing cohort involving cholangiocarcinoma patients with anti-PD-1 Sintilimab treatment after surgery was used to verify the potential application of the established radiomic model in immunotherapy for cholangiocarcinoma. Two distinct immune related subgroups were classified using ssGSEA based on transcriptome sequencing. For radiomic analysis, a total of 10 predictive radiomic features were finally identified to establish a radiomic signature model for immune landscape classification. Regarding to the predictive performance, the mean AUC of ROC curves was 0.80 in the training/validation cohort. For the independent testing cohort, the individual predictive probability by radiomic model and the corresponding immune score derived from ssGSEA was significantly correlated. In conclusion, radiomic signature model based on DCE-MRI was capable of predicting the immune landscape of chalangiocarcinoma. Consequently, a potentially clinical application of this developed radiomic model to guide immunotherapy for cholangiocarcinoma was suggested.

DNAJC24 acts directly with PCNA and promotes malignant progression of LUAD by activating phosphorylation of AKT.

Heat shock proteins (HSPs) are a group of highly conserved proteins found in a wide range of organisms. In recent years, members of the HSP family were overexpressed in various tumors and widely involved in oncogenesis, tumor development, and therapeutic resistance. In our previous study, DNAJC24, a member of the DNAJ/HSP40 family of HSPs, was found to be closely associated with the malignant phenotype of hepatocellular carcinoma. However, its relationship with other malignancies needs to be further explored. Herein, we demonstrated that DNAJC24 exhibited upregulated expression in LUAD tissue samples and predicted poor survival in LUAD patients. The upregulation of DNAJC24 expression promoted proliferation and invasion of LUAD cells in A549 and NCI-H1299 cell lines. Further studies revealed that DNAJC24 could regulate the PI3K/AKT signaling pathway by affecting AKT phosphorylation. In addition, a series of experiments such as Co-IP and mass spectrometry confirmed that DNAJC24 could directly interact with PCNA and promoted the malignant phenotypic transformation of LUAD. In conclusion, our results suggested that DNAJC24 played an important role in the progression of LUAD and may serve as a specific prognostic biomarker for LUAD patients. The DNAJC24/PCNA/AKT axis may be a potential target for future individualized and precise treatment of LUAD patients.

Preoperative CECT-Based Multitask Model Predicts Peritoneal Recurrence and Disease-Free Survival in Advanced Ovarian Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: Peritoneal recurrence is the predominant pattern of recurrence in advanced ovarian cancer (AOC) and portends a dismal prognosis. Accurate prediction of peritoneal recurrence and disease-free survival (DFS) is crucial to identify patients who might benefit from intensive treatment. We aimed to develop a predictive model for peritoneal recurrence and prognosis in AOC. METHODS: In this retrospective multi-institution study of 515 patients, an end-to-end multi-task convolutional neural network (MCNN) comprising a segmentation convolutional neural network (CNN) and a classification CNN was developed and tested using preoperative CT images, and MCNN-score was generated to indicate the peritoneal recurrence and DFS status in patients with AOC. We evaluated the accuracy of the model for automatic segmentation and predict prognosis. RESULTS: The MCNN achieved promising segmentation performances with a mean Dice coefficient of 84.3% (range: 78.8%-87.0%). The MCNN was able to predict peritoneal recurrence in the training (AUC 0.87; 95% CI 0.82-0.90), internal test (0.88; 0.85-0.92), and external test set (0.82; 0.78-0.86). Similarly, MCNN demonstrated consistently high accuracy in predicting recurrence, with an AUC of 0.85; 95% CI 0.82-0.88, 0.83; 95% CI 0.80-0.86, and 0.85; 95% CI 0.83-0.88. For patients with a high MCNN-score of recurrence, it was associated with poorer DFS with P < 0.0001 and hazard ratios of 0.1964 (95% CI: 0.1439-0.2680), 0.3249 (95% CI: 0.1896-0.5565), and 0.3458 (95% CI: 0.2582-0.4632). CONCLUSION: The MCNN approach demonstrated high performance in predicting peritoneal recurrence and DFS in patients with AOC.

Eosinophilic Solid and Cystic Renal Cell Carcinoma: Morphologic and Immunohistochemical Study of 18 Cases and Review of the Literature.

CONTEXT.­: Eosinophilic solid and cystic renal cell carcinoma is now defined in the 5th edition of the 2022 World Health Organization classification of urogenital tumors. OBJECTIVE.­: To perform morphologic, immunohistochemical, and preliminary genetic studies about this new entity in China for the purpose of understanding it better. DESIGN.­: The study includes 18 patients from a regional tertiary oncology center in northern China (Tianjin, China). We investigated the clinical and immunohistochemical features of these cases. RESULTS.­: The mean age of patients was 49.6 years and the male to female ratio was 11:7. Macroscopically, 1 case had the classic cystic and solid appearance whereas the others appeared purely solid. Microscopically, all 18 tumors shared similar solid and focal macrocystic or microcystic growth pattern, and the cells were characterized by voluminous and eosinophilic cytoplasm, along with coarse amphophilic stippling. Immunohistochemically, most of the tumors had a predominant cytokeratin (CK) 20-positive feature, ranging from focal cytoplasmic staining to diffuse membranous accentuation. Initially, we separated these cases into different immunohistochemical phenotypes. Group 1 (7 of 18; 38.5%) was characterized by positive phospho-4EBP1 and phospho-S6, which can imply hyperactive mechanistic target of rapamycin complex 1 (mTORC1) signaling. Group 2 (4 of 18; 23%) was negative for NF2, probably implying a germline mutation of NF2. Group 3 (7 of 18; 38.5%) consisted of the remaining cases. One case had metastatic spread and exhibited an aggressive clinical course, and we detected cyclin-dependent kinase inhibitor 2A (CDKN2A) mutation in this case; other patients were alive and without disease progression. CONCLUSIONS.­: Our research proposes that eosinophilic solid and cystic renal cell carcinoma exhibits prototypical pathologic features with CK20 positivity and has aggressive potential.

Corrigendum: An ultrasonic-based radiomics nomogram for distinguishing between benign and malignant solid renal masses.

[This corrects the article DOI: 10.3389/fonc.2022.847805.].

Autophagy Inhibition Contributes to Apoptosis of PLK4 Downregulation-induced Dormant Cells in Colorectal Cancer.

Dormant cancer cells account for cancer recurrence, distant metastasis and drug resistance which lead to poor prognosis in colorectal cancer (CRC). However, little is known about the molecular mechanisms regulating tumor cell dormancy and how to eliminate dormant cancer cells. Recent studies indicate autophagy affects dormant tumor cell survival. Here, we found that polo-like kinases 4 (PLK4), a central regulator of the cell cycle and proliferation, plays a crucial role in regulating CRC cells dormancy both in vitro and in vivo. Downregulation of PLK4 induced dormancy and inhibited migration and invasion in different CRC cell lines. Clinically, PLK4 expression was correlated with the dormancy markers (Ki67, p-ERK, p-p38) and late recurrence in CRC tissues. Mechanistically, downregulation of PLK4 induced autophagy contributed to restoring phenotypically aggressive tumor cells to a dormant state through the MAPK signaling pathway, and inhibition of autophagy would trigger apoptosis of dormant cells. Our findings reveal that downregulation of PLK4-induced autophagy contributes to tumor dormancy and autophagy inhibition leads to apoptosis of CRC dormant cells. Our study is the first to report that downregulation PLK4 induced autophagy is an early event in CRC dormancy and highlights autophagy inhibitor as a potential therapeutic target for dormant cell elimination.

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study.

RATIONALE AND OBJECTIVES: Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian cancer (OC) is essential for personalized medicine. We aimed to develop and validate a deep learning (DL) model based on pretreatment contrast-enhanced CT (CECT) images for predicting NACT responses and classifying high-grade serous ovarian cancer (HGSOC) to identify patients who may benefit from NACT. MATERIALS AND METHODS: This multicenter study, which contained both retrospective and prospective studies, included consecutive OC patients (n = 757) from three hospitals. Using WHO RECIST 1.1 for the reference standard, a total of 587 women with 1761 images were included in the training and validation sets, 67 women with 201 images were included in the prospective sets, and 103 women with 309 images were included in the external sets. A multitask DL model based on the multiperiod CT image was developed to predict NACT response and HGSOC. RESULTS: Logistic regression analysis showed that peritoneal invasion, retinal invasion, and inguinal lymph node metastasis were independent predictors. The DL achieved promising segmentation performances with DICEmean= 0.83 (range: 0.78-0.87). For predicting NACT response, the DL model combined with clinical risk factors obtained area under the receiver operating characteristic curve (AUCs) of 0.87 (0.83-0.89), 0.88 (0.86-0.91), 0.86 (0.82-0.89), and 0.79 (0.75-0.82) in the training, validation, prospective, and external sets, respectively. The AUCs were 0.91 (0.87-0.94), 0.89 (0.86-0.91), 0.80 (0.76-0.84), and 0.80 (0.75-0.85) in four sets in HGSOC classification. CONCLUSION: The multitask DL model developed using multiperiod CT images exhibited a promising performance for predicting NACT response and HGSOC with OC, which could provide valuable information for individualized treatment.

Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence.

BACKGROUND: Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis. METHODS: We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data. RESULTS: Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients. CONCLUSION: Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.

Clear cell renal cell carcinoma with cystic component similar to multilocular cystic renal neoplasm of low malignant potential: a rare pattern of cyst-dependent progression from multilocular cystic renal neoplasm of low malignant potential.

BACKGROUND: For clear cell renal cell carcinoma (ccRCC) with cystic component similar to multilocular cystic renal neoplasm of low malignant potential (MCRN-LMP) and solid low-grade component simultaneously, we propose the designation "ccRCC with cystic component similar to MCRN-LMP" and to study the relationship between MCRN-LMP and it. METHODS: Twelve cases of MCRN-LMP and 33 cases of ccRCC with cystic component similar to MCRN-LMP were collected from 3,265 consecutive RCCs to compare them in clinicopathological features, immunohistochemical findings (PAX8, CA-IX, CK7, Vimentin, CD10, P504s, TFE3, 34ßE12) and prognosis. RESULTS: There was no significant difference in age, sex ratio, tumor size, treatment, grade and stage between them (P > 0.05). All ccRCCs with cystic component similar to MCRN-LMP coexisted with MCRN-LMP and solid low-grade ccRCCs, and MCRN-LMP component ranged from 20 to 90% (median, 59%). The positive ratio of CK7 and 34ßE12 in MCRN-LMPs and ccRCCs' cystic parts was significantly higher than that in ccRCCs' solid parts, but the positive ratio of CD10 in MCRN-LMPs and ccRCCs' cystic parts was significantly lower than that in ccRCCs' solid parts (P < 0.05). There was no significant difference of all immunohistochemistry profiles between MCRN-LMPs and ccRCCs' cystic parts (P > 0.05). No patient developed recurrence or metastasis. CONCLUSIONS: MCRN-LMP and ccRCC with cystic component similar to MCRN-LMP have similarity and homology in clinicopathological features, immunohistochemical findings and prognosis, and form a low-grade spectrum with indolent or low malignant potential behavior. The ccRCC with cystic component similar to MCRN-LMP may be a rare pattern of cyst-dependent progression from MCRN-LMP.

CD73, a Promising Therapeutic Target of Diclofenac, Promotes Metastasis of Pancreatic Cancer through a Nucleotidase Independent Mechanism.

CD73, a cell surface-bound nucleotidase, facilitates extracellular adenosine formation by hydrolyzing 5'-AMP to adenosine. Several studies have shown that CD73 plays an essential role in immune escape, cell proliferation and tumor angiogenesis, making it an attractive target for cancer therapies. However, there are limited clinical benefits associated with the mainstream enzymatic inhibitors of CD73, suggesting that the mechanism underlying the role of CD73 in tumor progression is more complex than anticipated, and further investigation is necessary. In this study, CD73 is found to overexpress in the cytoplasm of pancreatic ductal adenocarcinoma (PDAC) cells and promotes metastasis in a nucleotidase-independent manner, which cannot be restrained by the CD73 monoclonal antibodies or small-molecule enzymatic inhibitors. Furthermore, CD73 promotes the metastasis of PDAC by binding to the E3 ligase TRIM21, competing with the Snail for its binding site. Additionally, a CD73 transcriptional inhibitor, diclofenac, a non-steroidal anti-inflammatory drug, is more effective than the CD73 blocking antibody for the treatment of PDAC metastasis. Diclofenac also enhances the therapeutic efficacy of gemcitabine in the spontaneous KPC (LSL-KrasG12D/+ , LSL-Trp53R172H/+ , and Pdx-1-Cre) pancreatic cancer model. Therefore, diclofenac may be an effective anti-CD73 therapy, when used alone or in combination with gemcitabine-based chemotherapy regimen, for metastatic PDAC.

ABO blood groups and expression of blood group antigens of epithelial ovarian cancer in Chinese women.

BACKGROUND: ABO blood groups has been associated with risk of several cancers; however, the results for an association with ovarian cancer are inconsistent and little is known about the expression of histo-blood group (ABH) antigens and ABO gene in ovarian tumor tissues. METHODS: To assess the impact of genotype-derived ABO blood types on the risk of EOC, we conducted a case-control study in 1,870 EOC and 4,829 controls. Expression of A and B antigen in 70 pairs of ovarian tumor tissues and adjacent normal tissues were detected by immunohistochemistry. Gene expression and DNA methylation profiling was conducted in ovarian tumor tissues. RESULTS: We identified that blood group A was associated with increased risk for EOC compared to blood group O (OR = 1.18, 95% CI = 1.03-1.36, p = 0.019). Increased frequency of aberrant expression of histo-blood group antigens was observed in patients with blood group A (76.5%) compared to patients with blood group O (21.1%) and B (5.0%) by immunohistochemistry (p < 0.001). ABO gene expression was down-regulated in ovarian tumor tissues compared with paired adjacent normal tissues (p = 0.027). In addition, ABO gene expression was positively correlated with NFYB (r = 0.38, p < 0.001) and inversely correlated with DNA methylation level of four CpG sites on ABO gene (cg11879188, r = - 0.3, p = 0.002; cg22535403, r = - 0.30, p = 0.002; cg13506600, r = - 0.22, p = 0.025; cg07241568, r = - 0.21, p = 0.049) in ovarian tumor tissues. CONCLUSION: We identified blood group A was associated with increased EOC risk in Chinese women and provided the clues of the possible molecular mechanisms of blood group A related to ovarian cancer risk.

PNO1 inhibits autophagy-mediated ferroptosis by GSH metabolic reprogramming in hepatocellular carcinoma.

Effective strategies for hepatocellular carcinoma, which is the second leading cause of death worldwide, remain limited. A growing body of emerging evidence suggests that ferroptosis activation is a novel promising approach for the treatment of this malignancy. Nevertheless, the potential therapeutic targets and molecular mechanisms of ferroptosis remain elusive. In this study, we found that PNO1 is a bona fide inhibitor of ferroptosis and that autophagy induced by PNO1 promotes cystine/glutamate antiporter SLC7A11 while increasing the synthesis and accumulation of intracellular glutamate. This increase is followed by an equally proportional addition in cystine uptake, which consequently enhances system Xc- activity that leads to the inhibition of ferroptosis. In the maintenance of redox homeostasis, system Xc- activated via PNO1-autophagy metabolism is responsible for maintaining cysteine for glutathione (GSH) synthesis, and the final GSH metabolic reprogramming protects HCC cells from ferroptosis. The combination of PNO1 inhibition with drugs causing ferroptosis induction, particularly sorafenib, the first-line drug associated with ferroptosis in liver cancer shows therapeutic promise in vitro and in vivo. Together, our findings indicated that PNO1 protects HCC cells from ferroptotic death through autophagy-mediated GSH metabolic remodeling, and we identified a candidate therapeutic target that may potentiate the effect of ferroptosis-based antitumor therapy.

Pathologic responses to neoadjuvant chemoimmunotherapy in primary limited-stage small-cell lung cancer.

BACKGROUND: Immunotherapy has been proved to have a large effect on extensive-stage small cell lung cancer, but the role of immunotherapy in limited-stage small-cell lung cancer (LS-SCLC) is still unknown. METHODS: A retrospective study of six patients with LS-SCLC who were treated with neoadjuvant chemoimmunotherapy (durvalumab plus etoposide combined with cisplatin) was performed. Patients were evaluated by the safety, feasibility and pathologic responses of neoadjuvant chemoimmunotherapy. RESULTS: Neoadjuvant durvalumab combined chemotherapy was associated with few immediate adverse events and did not delay planned surgery. All patients achieved partial pathologic response (pPR) instead of major pathologic response, or pathologic complete response. No association was observed between programmed death-ligand 1 expression in tumor specimens and the pathologic response. However, tumors with high expression of immune cells such as CD4+ T cells, CD8+ T cells and FoxP3+ Tregs tended to have better pathologic responses than tumors with low expression of immune cells. CONCLUSIONS: Neoadjuvant durvalumab combined chemotherapy could induce pPR with few side effects in resectable LS-SCLC. The immune cells in the tumor microenvironment might play an important role in neoadjuvant chemoimmunotherapy in resectable LS-SCLC.

Low expression and Hypermethylation of ATP2B1 in Intrahepatic Cholangiocarcinoma Correlated With Cold Tumor Microenvironment.

Background: The efficacy of current therapeutic schedule is limited owing to fibroproliferative tumor microenvironment (TME) of cholangiocarcinoma, compelling a search for new therapeutic targets. Methods: Gene expression profiles and methylation profiles were obtained from UCSC Xena. Consensus clustering was performed on the transcriptome data of cholangiocarcinoma to determine the different immune subtypes. The differentially expressed genes (DEGs) between hot tumor and cold tumors were identified. ESTIMATE was used to assess immune score, and the cases were separated into relatively superior and inferior immune score groups. Single-sample gene set enrichment analysis was applied to assess 28 immune cells in the cholangiocarcinoma microenvironment. Unsupervised consensus was applied for methylation profiling to distribute the high and low methylation groups. The correlation between DNA methylation and mRNA expression was investigated, and the relationship between the ATP2B1 gene and the immune microenvironment was explored. Finally, 77 cases of intrahepatic cholangiocarcinoma (ICC) were collected for verification. Results: Seven subtypes were related to patient outcomes (P=0.005). The proportions of CD8+ T cells in the "hot" immune type was significantly greater than that in the "cold" immune type (P<0.05). Next, DEGs and DNA methylation-governed genes were intersected, and ATP2B1 was identified as a prognosis factor in ICC (P=0.035). ATP2B1 expression was positively correlated with immune scores (P=0.005, r=0.458), the levels of infiltrating CD8+ T cells (P=0.004, r=0.47), and CD4+ T cells (P=0.027, r=0.37). Immunohistochemistry confirmed that the amounts of CD8+ and CD4+ T cells were significantly higher in ICC tissue samples than in tissues with ATP2B1 overexpression (P<0.05). Conclusions: ATP2B1 overexpression can activate immune signals and prompt cold tumor response.

A Single-Cell Atlas of Tumor-Infiltrating Immune Cells in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with limited treatment options. To guide the design of more effective immunotherapy strategies, mass cytometry was employed to characterize the cellular composition of the PDAC-infiltrating immune cells. The expression of 33 protein markers was examined at the single-cell level in more than two million immune cells from four types of clinical samples, including PDAC tumors, normal pancreatic tissues, chronic pancreatitis tissues, and peripheral blood. Based on the analyses, we identified 23 distinct T-cell phenotypes, with some cell clusters exhibiting aberrant frequencies in the tumors. Programmed cell death protein 1 (PD-1) was extensively expressed in CD4+ and CD8+ T cells and coexpressed with both stimulatory and inhibitory immune markers. In addition, we observed elevated levels of functional markers, such as CD137L and CD69, in PDAC-infiltrating immune cells. Moreover, the combination of PD-1 and CD8 was used to stratify PDAC tumors from The Cancer Genome Atlas database into three immune subtypes, with S1 (PD-1+CD8+) exhibiting the best prognosis. Further analysis suggested distinct molecular mechanisms for immune exclusion in different subtypes. Taken together, the single-cell protein expression data depicted a detailed cell atlas of the PDAC-infiltrating immune cells and revealed clinically relevant information regarding useful cell phenotypes and targets for immunotherapy development.

DNAJC24 is a potential therapeutic target in hepatocellular carcinoma through affecting ammonia metabolism.

Evolutionarily conserved heat shock proteins are involved in the heat shock response of cells in response to changes in the external environment. In normal tissues, heat shock proteins can help cells survive in a rapidly changing environment. Likewise, in malignant tumors heat shock proteins may help tumor cells cope with external stresses as well as the stress of treatment. In this way they become accomplices of malignant tumors. Here we demonstrated for the first time that high expression of DNAJC24 (a heat shock protein) shortens survival in patients with HCC by immunohistochemical staining of 167 paired hepatocellular carcinomas and paraneoplastic tissues as well as data from public databases. In vitro experiments demonstrated that stimuli such as hypoxia, starvation and heat could upregulate DNAJC24 expression in HCC cells through transcriptional regulation of HSF2, and high expression of DNAJC24 in HCC cells could promote the proliferation and motility of HCC cells. In addition, we also verified that targeting DNAJC24 under normal culture conditions can affect the proliferation and autophagy of HCC cells by interfering with ammonia metabolism, thereby inhibiting the malignant progression of HCC. Overall, we suggested that DNAJC24 may become a new target for the treatment of HCC.

An Ultrasonic-Based Radiomics Nomogram for Distinguishing Between Benign and Malignant Solid Renal Masses.

Objectives: This study was conducted in order to develop and validate an ultrasonic-based radiomics nomogram for diagnosing solid renal masses. Methods: Six hundred renal solid masses with benign renal lesions (n = 204) and malignant renal tumors (n = 396) were divided into a training set (n = 480) and a validation set (n = 120). Radiomics features were extracted from ultrasound (US) images preoperatively and then a radiomics score (RadScore) was calculated. By integrating the RadScore and independent clinical factors, a radiomics nomogram was constructed. The diagnostic performance of junior physician, senior physician, RadScore, and radiomics nomogram in identifying benign from malignant solid renal masses was evaluated based on the area under the receiver operating characteristic curve (ROC) in both the training and validation sets. The clinical usefulness of the nomogram was assessed using decision curve analysis (DCA). Results: The radiomics signature model showed satisfactory discrimination in the training set [area under the ROC (AUC), 0.887; 95% confidence interval (CI), 0.860-0.915] and the validation set (AUC, 0.874; 95% CI, 0.816-0.932). The radiomics nomogram also demonstrated good calibration and discrimination in the training set (AUC, 0.911; 95% CI, 0.886-0.936) and the validation set (AUC, 0.861; 95% CI, 0.802-0.921). In addition, the radiomics nomogram model showed higher accuracy in discriminating benign and malignant renal masses compared with the evaluations by junior physician (DeLong p = 0.004), and the model also showed significantly higher specificity than the senior and junior physicians (0.93 vs. 0.57 vs. 0.46). Conclusions: The ultrasonic-based radiomics nomogram shows favorable predictive efficacy in differentiating solid renal masses.

Single-Cell DNA Sequencing Reveals Punctuated and Gradual Clonal Evolution in Hepatocellular Carcinoma.

BACKGROUND & AIMS: Copy number alterations (CNAs), elicited by genome instability, are a major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma (HCC) remains unknown. METHODS: We performed single-cell DNA sequencing (scDNA-seq) on 1275 cells isolated from 10 patients with HCC, ploidy-resolved scDNA-seq on 356 cells from 1 additional patient, and single-cell RNA sequencing on 27,344 cells from 3 additional patients. Three statistical fitting models were compared to investigate the CNA accumulation pattern. RESULTS: Cells in the tumor were categorized into the following 3 subpopulations: euploid, pseudoeuploid, and aneuploid. Our scDNA-seq analysis revealed that CNA accumulation followed a dual-phase copy number evolution model, that is, a punctuated phase followed by a gradual phase. Patients who exhibited prolonged gradual phase showed higher intratumor heterogeneity and worse disease-free survival. Integrating bulk RNA sequencing of 17 patients with HCC, published datasets of 1196 liver tumors, and immunohistochemical staining of 202 HCC tumors, we found that high expression of CAD, a gene involved in pyrimidine synthesis, was correlated with rapid tumorigenesis and reduced survival. The dual-phase copy number evolution model was validated by our single-cell RNA sequencing data and published scDNA-seq datasets of other cancer types. Furthermore, ploidy-resolved scDNA-seq revealed the common clonal origin of diploid- and polyploid-aneuploid cells, suggesting that polyploid tumor cells were generated by whole genome doubling of diploid tumor cells. CONCLUSIONS: Our work revealed a novel dual-phase copy number evolution model, showed HCC with longer gradual phase was more severe, identified CAD as a promising biomarker for early recurrence of HCC, and supported the diploid origin of polyploid HCC.

Prognostic value of desmoplastic stromal reaction, tumor budding and tumor-stroma ratio in stage II colorectal cancer.

Background: Existing high-risk factors are insufficient to accurately predict the postoperative recurrence risk of stage II colorectal cancer (CRC). The discovery of additional prognostic markers may be the key to improving the current status of stage II CRC treatment. The present study aimed to evaluate the relationship among desmoplastic reaction (DR), tumor budding (TBd), the tumor-stroma ratio (TSR) and their prognostic value for relapse-free survival (RFS). Methods: In this study, 207 patients with histologically confirmed stage II CRC from January 2012 to August 2018 were retrospectively reviewed from a single center; the cohort was divided into subgroups based on low or high TSR, and low, intermediate or high DR and TBd. Kaplan-Meier curve analysis and log-rank test were applied to examine RFS among subgroups. Univariate and multivariate Cox proportional hazards analyses were used to identify independent factors associated with RFS, and a nomogram was subsequently developed. Results: Abnormal CA242, CEA, T4 stage, presence of hypertension, internal obstruction or perforation (IOP), lymphovascular or/and perineural invasion (PNI), number of nodes examined less than 12, low-frequency microsatellite instability (MSI-L), higher Ki-67 and immature DR were associated with a lower RFS. In multivariable analysis, DR (HR =2.111; 95% CI: 1.184-3.766; P=0.011), LVI (HR =1.919; 95% CI: 1.004-3.669; P=0.049) and PNI (HR =2.724; 95% CI: 1.362-5.448; P=0.005) were prognostic factors for RFS. On this basis, a nomogram that integrated DR and clinicopathologic predictors for predicting RFS passed the calibration and had an area under the curve of 0.826. Conclusions: The prognostic significance of DR outperformed TBd and TSR, therefore, we recommend adding DR as a biomarker in routine pathological reports. The novel nomogram combining these factors may be used as a reliable and effective tool for the prediction of RFS in stage II CRC, thus helping optimize therapeutic regimens under cooperation of oncologists and surgeons. Further multicentric studies are required for validation of this novel, simple and cost-effective prognostic model.

Diagnosis of Ovarian Neoplasms Using Nomogram in Combination With Ultrasound Image-Based Radiomics Signature and Clinical Factors.

Objectives: To establish and validate a nomogram integrating radiomics signatures from ultrasound and clinical factors to discriminate between benign, borderline, and malignant serous ovarian tumors. Materials and methods: In this study, a total of 279 pathology-confirmed serous ovarian tumors collected from 265 patients between March 2013 and December 2016 were used. The training cohort was generated by randomly selecting 70% of each of the three types (benign, borderline, and malignant) of tumors, while the remaining 30% was included in the validation cohort. From the transabdominal ultrasound scanning of ovarian tumors, the radiomics features were extracted, and a score was calculated. The ability of radiomics to differentiate between the grades of ovarian tumors was tested by comparing benign vs borderline and malignant (task 1) and borderline vs malignant (task 2). These results were compared with the diagnostic performance and subjective assessment by junior and senior sonographers. Finally, a clinical-feature alone model and a combined clinical-radiomics (CCR) model were built using predictive nomograms for the two tasks. Receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA) were performed to evaluate the model performance. Results: The US-based radiomics models performed satisfactorily in both the tasks, showing especially higher accuracy in the second task by successfully discriminating borderline and malignant ovarian serous tumors compared to the evaluations by senior sonographers (AUC = 0.789 for seniors and 0.877 for radiomics models in task one; AUC = 0.612 for senior and 0.839 for radiomics model in task 2). We showed that the CCR model, comprising CA125 level, lesion location, ascites, and radiomics signatures, performed the best (AUC = 0.937, 95%CI 0.905-0.969 in task 1, AUC = 0.924, 95%CI 0.876-0.971 in task 2) in the training as well as in the validation cohorts (AUC = 0.914, 95%CI 0.851-0.976 in task 1, AUC = 0.890, 95%CI 0.794-0.987 in task 2). The calibration curve and DCA analysis of the CCR model more accurately predicted the classification of the tumors than the clinical features alone. Conclusion: This study integrates novel radiomics signatures from ultrasound and clinical factors to create a nomogram to provide preoperative diagnostic information for differentiating between benign, borderline, and malignant ovarian serous tumors, thereby reducing unnecessary and risky biopsies and surgeries.