Proliferation marker Ki-67 in early breast cancer

Epithelial‑derived head and neck squamous tumourigenesis (Review)

Head and neck squamous cell carcinomas (HNSCCs), a heterogeneous group of cancers that arise from the mucosal epithelia cells in the head and neck areas, present great challenges in diagnosis, treatment and prognosis due to their complex aetiology and various clinical manifestations. Several factors, including smoking, alcohol consumption, oncogenic genes, growth factors, Epstein‑Barr virus and human papillomavirus infections can contribute to HNSCC development. The unpredictable tumour microenvironment adds to the complexity of managing HNSCC. Despite significant advances in therapies, the prediction of outcome after treatment for patients with HNSCC remains poor, and the 5‑year overall survival rate is low due to late diagnosis. Early detection greatly increases the chances of successful treatment. The present review aimed to bring together the latest findings related to the molecular mechanisms of HNSCC carcinogenesis and progression. Comprehensive genomic, transcriptomic, metabolomic, microbiome and proteomic analyses allow researchers to identify important biological markers such as genetic alterations, gene expression signatures and protein markers that drive HNSCC tumours. These biomarkers associated with the stages of initiation, progression and metastasis of cancer are useful in the management of patients with cancer in order to improve their life expectancy and quality of life.

Combination of US hyperthermia and radiotherapy on a preclinical glioblastoma model

In this work the effect of combining ultrasound (US) hyperthermia (HT) with radiotherapy (RT) was investigated. The treatment was applied to a GBM xenograft nude mouse model obtained by injecting 2 × 10 6 U87 luc+ cells. The combined treatment group received 6 Gy and HT at 43 ∘ for 8 min. The ultrasound field was generated by a closed-loop computationally controlled system, consisting of a High Intensity Focused Ultrasound (HIFU) transducer with centre frequency 3.57 MHz, a power amplifier, a function generator and a MATLAB controller. A mechanical cone adaptor has been designed to use the HIFU beam at a pre-defined post-focal distance. Two thermocouples were placed between the mechanical cone and the mice skin to measure and control the temperature during the HT treatment. Radiotherapy was carried out by using a dedicated small animal image guided radiotherapy system. Measurements of tumor volume performed with a caliper showed good tumor control for the RT-HT group with respect to the RT or control groups for up to 21 days after treatment. The mean value of the normalized (before therapy) tumor volume was almost equal to 0.5 for two weeks after treatment with an increase to 1.5 at sacrifice. The control and HT groups showed a higher value of about 1.5 during the first two weeks and 3.5 at the end of the follow-up period. We concluded that the use of HT as a radiosensitizer can improve the outcome for glioblastoma treatments.

Discovery of novel small molecules targeting the USP21/JAK2/STAT3 axis for the treatment of triple-negative breast cancer

The deficiency in available targeted agents and frequency of chemoresistance are primary challenges in clinical management of triple-negative breast cancer (TNBC). The aberrant expression of USP21 and JAK2 represents a characterized mechanism of TNBC progression and resistance to paclitaxel (PTX). Despite its clear that high expression of USP21-mediated de-ubiquitination leads to increased levels of JAK2 protein, we lack regulator molecules to dissect the mechanisms that the interaction between USP21 and JAK2 contributes to the phenotype and resistance of TNBC. Here, we report a USP21/JAK2/STAT3 axis-targeting regulator 13c featuring a N-anthraniloyl tryptamine scaffold that showed excellent anti-TNBC potency and promising safety profile. Importantly, the therapeutic potential of using 13c in combination with PTX in PTX-resistant TNBC was demonstrated. This study showcases N-anthraniloyl tryptamine derivatives as a novel anti-TNBC chemotype with a pharmacological mode of action targeting the USP21/JAK2/STAT3 axis and provides a potential therapeutic target for the treatment of TNBC.

Assessment of the Predictive Role of Ki-67 in Breast Cancer Patients' Responses to Neoadjuvant Chemotherapy

OBJECTIVE

Neoadjuvant chemotherapy (NAC) in breast cancer (BC) is being considered for a broader range of cases, including locally advanced tumors and situations where downstaging could reduce extensive surgery. Several trials have explored predictive markers of pathological complete response (pCR). The role of Ki-67 as a predictor of pCR has been demonstrated in studies. However, the cut-off remains vague, given the lack of standardization of measurement methods. The aim of our study was to evaluate the predictive value of Ki-67 in response to NAC and to identify the cut-off values that exhibit the strongest correlation with best response.

MATERIALS AND METHODS

This retrospective study included 187 patients who had undergone surgery following NAC for BC at the CHU Souss Massa of Agadir between January 2020 and January 2023. Logistic regression was used to assess the correlation between Ki-67 and patients' characteristics. Optimal Ki-67 cutoff was identified by receiver operating characteristic curve. Kaplan-Meier curves were used to assess disease-free survival (DFS), and survival comparisons were assessed with the log-rank test.

RESULTS

The median age was 51.8±10.7 years and 51.4% of tumors were smaller than 5 cm. Node invasion was found in 55.4%. Luminal B subtype was found in 49.7%, followed by human epidermal growth factor receptor-2 (HER-2)-positive in 27.4%, triple-negative in 14.3% and Luminal A in 8.6%. pCR occurred in 40% of patients overall. Subgroup analysis revealed a significant association between pCR and tumor size (p<0.001), lymph node involvement (p<0.001), grade 2 (p<0.001), vascular invasion (p<0.001), and positive HER-2 status (p = 0.022). In statistical analysis, pathological responses were improved in patients with Ki-67 >35% (p<0.001). DFS was 98.8% at 12 months. No statistical difference was found in DFS according to Ki-67 values and pCR status.

CONCLUSION

Our results indicate that Ki-67 is a predictive marker for response in the neoadjuvant setting in BC patients. Our study showed that a Ki-67 cut-off >35% predicts a better pCR rate in response to NAC. However, this cutoff value remains controversial due to the absence of a standard method of measurement, with inter- and intra-observer variability. It would be necessary to validate this cutoff in other studies.

Targeted drug-loaded peptides induce tumor cell apoptosis and immunomodulation to increase antitumor efficacy

Immunotherapy is an emerging approach for the treatment of solid tumors. Although chemotherapy is generally considered immunosuppressive, specific chemotherapeutic agents can induce tumor immunity. In this study, we developed a targeted, acid-sensitive peptide nanoparticle (DT/Pep1) to deliver doxorubicin (DOX) and triptolide (TPL) to breast cancer cells via the enhanced permeability and retention (EPR) effect and the breast cancer-targeting effect of peptide D8. Compared with administration of the free drugs, treatment with the DT/Pep1 system increased the accumulation of DOX and TPL at the tumor site and achieved deeper penetration into the tumor tissue. In an acidic environment, DT/Pep1 transformed from spherical nanoparticles to aggregates with a high aspect ratio, which successfully extended the retention of the drugs in the tumor cells and bolstered the anticancer effect. In both in vivo and in vitro experiments, DT/Pep1 effectively blocked the cell cycle and induced apoptosis. Importantly, the DT/Pep1 system efficiently suppressed tumor development in mice bearing 4T1 tumors while simultaneously promoting immune system activation. Thus, the results of this study provide a system for breast cancer therapy and offer a novel and promising platform for peptide nanocarrier-based drug delivery.

Clinical and Paraclinical Considerations Regarding ki67's Role in the Management of Differentiated Thyroid Carcinoma-A Literature Review

Background and Objectives: The ki67 nuclear protein is a tool for diagnosis and prognosis in oncology that is used to evaluate cell proliferation. Differentiated thyroid carcinoma is usually a slow-growing neoplasm, the most common type being the papillary form. Some clinical and pathological aspects may predict aggressive behaviour. There are reported cases of recurrence without clinico-pathological findings of aggressiveness. To obtain better predictions of the disease outcome in thyroid carcinoma, many immunohistochemical markers have been studied. The aim of this narrative literature review is to identify the benefits that ki67 may add to the management of patients with differentiated thyroid carcinoma, according to the latest evidence. Materials and Methods: We performed a search on the PubMed and Google Scholar databases using controlled vocabulary and keywords to find the most suitable published articles. A total number of sixty-eight items were identified, and five other articles were selected from other sources. After refining the selection, the inclusion criteria and exclusion criteria were applied, and a total number of twenty-nine articles were included in this literature review. Results and Discussion: The studies consist of retrospective studies (89.66%), case reports (6.9%) and literature reviews (3.45%), evaluating the role, implications and other parameters of ki67 as a diagnostic and/or prognostic tool. The statistical correlations between ki67 and other features were systematized as qualitative results of this review in order to improve the treatment strategies presented in the included articles. Conclusions: The included studies present converging data regarding most of the aspects concerning ki67. The ki67 proliferation index is a diagnostic/prognostic tool of interest in differentiated thyroid carcinoma and a good predictor of disease-free survival, disease recurrence and metastatic development. Prospective studies on large cohorts may add value for ki67 as a specific tool in the management strategy of differentiated thyroid carcinoma.

A novel multiscale framework for delineating cancer evolution from subclonal compositions

OBJECTIVE

Owing to the heterogeneity in the evolution of cancer, distinguishing between diverse growth patterns and predicting long-term outcomes based on short-term measurements poses a great challenge.

METHODS

A novel multiscale framework is proposed to unravel the connections between the population dynamics of cancer growth (i.e., aggressive, bounded, and indolent) and the cellular-subclonal dynamics of cancer evolution. This framework employs the non-negative lasso (NN-LASSO) algorithm to forge a link between an ordinary differential equation (ODE)-based population model and a cellular evolution model.

RESULTS

The findings of our current work not only affirm the impact of subclonal composition on growth dynamics but also identify two significant subclones within heterogeneous growth patterns. Moreover, the subclonal compositions at the initial time are able to accurately discriminate diverse growth patterns through a machine learning algorithm.

CONCLUSION

The proposed multiscale framework successfully delineates the intricate landscape of cancer evolution, bridging the gap between long-term growth dynamics and short-term measurements, both in simulated and real-world data. This methodology provides a novel avenue for thorough exploration into the realm of cancer evolution.

Comprehensive evaluation of the relationship between biomarker profiles and neoadjuvant chemotherapy outcomes for breast cancer patients

BACKGROUND

Accurately predicting the response to neoadjuvant chemotherapy (NAC) in breast cancer patients is crucial for guiding treatment strategies and enhancing clinical outcomes. Current studies have primarily focused on a limited set of biomarkers. More importantly, the results of many studies are in conflict. To address this, we conducted a comprehensive evaluation of the predictive value of a diverse range of clinically available molecular biomarkers in breast cancer, including HER2, ER, PR, TOPO II, EGFR, Ki67, CK5/6, AR, and p53. Additionally, we assessed changes in these biomarkers after NAC administration.

METHODS

Our study involved 189 patients with invasive breast cancer who underwent NAC at our institute. We examined biomarker profiles in core-needle biopsies taken before NAC and in surgical specimens obtained after NAC. We examined the association between these biomarkers and NAC outcomes, focusing on two main aspects: the rate of pathological complete response (pCR) and the reduction in tumor size. We used Chi-square and Mann-Whitney U tests to compare biomarker status changes between pCR and non-pCR patients. Linear regression analysis was employed to evaluate the relationship between biomarker status and tumor shrinkage rate. Additionally, we compared the expression status of these biomarkers before and after NAC using Chi-square and Wilcoxon signed-rank tests.

RESULTS AND CONCLUSIONS

Our results demonstrated significant differences in the expression levels of HER2, ER, PR, TOPO II, EGFR, and Ki67 between pCR and non-pCR patients, underscoring their potential as predictive markers for NAC outcomes. Importantly, our results have shed light on the contentious issue surrounding TOPO II in NAC outcome prediction. We have provided evidence that establishes a significantly positive association between TOPO II expression level and the pCR rate. Notably, tumor size was identified as a relevant predictive factor for achieving pCR. Regarding biomarker profiles, only Ki67 levels and TOPO II status exhibited changes following NAC, resolving previous controversies. While the ER and PR status remained unchanged, their expression values exhibited a slight but significant decrease post-NAC. Our results provide clarity and insights into the value and potential of using these biomarkers to predict NAC responses and prognosis in breast cancer patients.

Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application

In recent years, artificial intelligence (AI) has demonstrated exceptional performance in mitosis identification and quantification. However, the implementation of AI in clinical practice needs to be evaluated against the existing methods. This study is aimed at assessing the optimal method of using AI-based mitotic figure scoring in breast cancer (BC). We utilized whole slide images from a large cohort of BC with extended follow-up comprising a discovery (n = 1715) and a validation (n = 859) set (Nottingham cohort). The Cancer Genome Atlas of breast invasive carcinoma (TCGA-BRCA) cohort (n = 757) was used as an external test set. Employing automated mitosis detection, the mitotic count was assessed using 3 different methods, the mitotic count per tumor area (MCT; calculated by dividing the number of mitotic figures by the total tumor area), the mitotic index (MI; defined as the average number of mitotic figures per 1000 malignant cells), and the mitotic activity index (MAI; defined as the number of mitotic figures in 3 mm2 area within the mitotic hotspot). These automated metrics were evaluated and compared based on their correlation with the well-established visual scoring method of the Nottingham grading system and Ki67 score, clinicopathologic parameters, and patient outcomes. AI-based mitotic scores derived from the 3 methods (MCT, MI, and MAI) were significantly correlated with the clinicopathologic characteristics and patient survival (P < .001). However, the mitotic counts and the derived cutoffs varied significantly between the 3 methods. Only MAI and MCT were positively correlated with the gold standard visual scoring method used in Nottingham grading system (r = 0.8 and r = 0.7, respectively) and Ki67 scores (r = 0.69 and r = 0.55, respectively), and MAI was the only independent predictor of survival (P < .05) in multivariate Cox regression analysis. For clinical applications, the optimum method of scoring mitosis using AI needs to be considered. MAI can provide reliable and reproducible results and can accurately quantify mitotic figures in BC.

HER2-positive is an independent indicator for predicting pathological complete response to neoadjuvant therapy and Ki67-changed after neoadjuvant chemotherapy predicts favorable prognosis in Chinese women with locally advanced breast cancer

The growing body of evidence suggests that breast cancer (BC) who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) may experience a more favorable prognosis. The objective of this study is to investigate the correlation between clinicopathologic parameters of locally advanced breast cancer (LABC) patients and the outcomes of NAC, with the aim of identifying predictive indicators for pCR. Additionally, we seek to examine the conversion of IHC markers in pCR patients following NAC and its impact on the prognosis of BC patients. We conducted a study involving 126 patients with LABC. Clinicopathological parameters associated with pCR were subjected to univariate and multivariate analysis. Kaplan-Meier (KM) curves and the log-rank test were used to compare the statistical difference in prognosis in different groups of patients. Additionally, we used difference and consistency tests to examine the conversion of immunohistochemistry (IHC) markers following NAC. The status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and molecular subtypes of BC were associated with pCR in the univariate analysis (all P < .05), which may be potential markers to predict pCR. HER2 was identified as an independent factor for predicting pCR in the multivariate analysis. The pCR rate of HER2-positive patients who received NAC combined targeted therapy was higher than that of patients who only received NAC (P = .003). The disease-free survival (DFS) rate of TNBC patients who achieved pCR was significantly higher than that of non-pCR TNBC patients (P = .026). The IHC marker conversion after NAC mainly existed in PR (P = .041). Ki67 expression decreased in the luminal B subtype and increased in the HER2 enriched subtype after NAC (all P < .001). Patients with Ki67 expression change after NAC had longer overall survival (OS) and DFS than unchanged patients (all P < .05). HER2-positive is an independent indicator for predicting pCR, and HE2-positive patients who received NAC combined targeted therapy were favorable to achieving pCR. IHC markers of BC patients exhibit varying degrees of alterations after NAC, and changes in Ki67 expression after NAC could serve as a marker to predict a better prognosis.

Microfluidic Organoid Cultures Derived from Pancreatic Cancer Biopsies for Personalized Testing of Chemotherapy and Immunotherapy

Patient-derived cancer organoids (PDOs) hold considerable promise for personalizing therapy selection and improving patient outcomes. However, it is challenging to generate PDOs in sufficient numbers to test therapies in standard culture platforms. This challenge is particularly acute for pancreatic ductal adenocarcinoma (PDAC) where most patients are diagnosed at an advanced stage with non-resectable tumors and where patient tissue is in the form of needle biopsies. Here the development and characterization of microfluidic devices for testing therapies using a limited amount of tissue or PDOs available from PDAC biopsies is described. It is demonstrated that microfluidic PDOs are phenotypically and genotypically similar to the gold-standard Matrigel organoids with the advantages of 1) spheroid uniformity, 2) minimal cell number requirement, and 3) not relying on Matrigel. The utility of microfluidic PDOs is proven by testing PDO responses to several chemotherapies, including an inhibitor of glycogen synthase kinase (GSKI). In addition, microfluidic organoid cultures are used to test effectiveness of immunotherapy comprised of NK cells in combination with a novel biologic. In summary, our microfluidic device offers considerable benefits for personalizing oncology based on cancer biopsies and may, in the future, be developed into a companion diagnostic for chemotherapy or immunotherapy treatments.

AI improves accuracy, agreement and efficiency of pathologists for Ki67 assessments in breast cancer

The Ki-67 proliferation index (PI) guides treatment decisions in breast cancer but suffers from poor inter-rater reproducibility. Although AI tools have been designed for Ki-67 assessment, their impact on pathologists' work remains understudied. 90 international pathologists were recruited to assess the Ki-67 PI of ten breast cancer tissue microarrays with and without AI. Accuracy, agreement, and turnaround time with and without AI were compared. Pathologists' perspectives on AI were collected. Using AI led to a significant decrease in PI error (2.1% with AI vs. 5.9% without AI, p < 0.001), better inter-rater agreement (ICC: 0.70 vs. 0.92; Krippendorff's α: 0.63 vs. 0.89; Fleiss' Kappa: 0.40 vs. 0.86), and an 11.9% overall median reduction in turnaround time. Most pathologists (84%) found the AI reliable. For Ki-67 assessments, 76% of respondents believed AI enhances accuracy, 82% said it improves consistency, and 83% trust it will improve efficiency. This study highlights AI's potential to standardize Ki-67 scoring, especially between 5 and 30% PI-a range with low PI agreement. This could pave the way for a universally accepted PI score to guide treatment decisions, emphasizing the promising role of AI integration into pathologist workflows.

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning

BACKGROUND

Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy.

METHODS

In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs).

RESULTS

We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts.

CONCLUSION

The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-based biomarkers for research purposes.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Extracellular Vesicles in Triple-Negative Breast Cancer: Immune Regulation, Biomarkers, and Immunotherapeutic Potential

Triple-negative breast cancer (TNBC) is an aggressive subtype accounting for ~10-20% of all human BC and is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) amplification. Owing to its unique molecular profile and limited targeted therapies, TNBC treatment poses significant challenges. Unlike other BC subtypes, TNBC lacks specific molecular targets, rendering endocrine therapies and HER2-targeted treatments ineffective. The chemotherapeutic regimen is the predominant systemic treatment modality for TNBC in current clinical practice. However, the efficacy of chemotherapy in TNBC is variable, with response rates varying between a wide range of patients, and the emerging resistance further adds to the difficulties. Furthermore, TNBC exhibits a higher mutational burden and is acknowledged as the most immunogenic of all BC subtypes. Consequently, the application of immune checkpoint inhibition has been investigated in TNBC, yielding promising outcomes. Recent evidence identified extracellular vesicles (EVs) as an important contributor in the context of TNBC immunotherapy. In view of the extraordinary ability of EVs to transfer bioactive molecules, such as proteins, lipids, DNA, mRNAs, and small miRNAs, between the cells, EVs are considered a promising diagnostic biomarker and novel drug delivery system among the prospects for immunotherapy. The present review provides an in-depth understanding of how EVs influence TNBC progression, its immune regulation, and their contribution as a predictive biomarker for TNBC. The final part of the review focuses on the recent key advances in immunotherapeutic strategies for better understanding the complex interplay between EVs and the immune system in TNBC and further developing EV-based targeted immunotherapies.

The POWER-PAK Score Characterizes Tumor Response to 3 Months of Preoperative Endocrine Therapy

BACKGROUND

The Pre-Operative Window of Endocrine Therapy to Inform Radiation Therapy Decisions (POWER, NCT04272801) trial aims to determine whether 3 months of preoperative endocrine therapy (pre-ET) informs adjuvant radiation therapy decisions among older women with early stage, ER-positive breast cancer. We propose the POWER Pathologic Assessment and Ki-67 (POWER-PAK) scoring system to characterize the histologic effects of pre-ET.

METHODS

Histologic evaluation was performed on core biopsy and lumpectomy specimens from 37 POWER trial participants who completed pre-ET and surgery. The POWER-PAK score consists of tumor regression, decrease in Ki-67 expression, and ER expression, each ranging from 0 to 2. Scores were aggregated to create the POWER-PAK score with a range from 0 to 6. Participants with no residual tumor were labelled 6-NRT.

RESULTS

ER expression did not decrease after pre-ET. Ki-67 decreased from 13% in biopsy specimens to 5% in the lumpectomy specimens (p < 0.001). Cellularity decreased from 40% to 23% (p < 0.001). There was heterogeneity of POWER-PAK scores ranging from 2 to 6-NRT: score of 2, n = 2 (5.4%); 4, n = 8 (21.6%); 5, n = 4 (10.8%); 6, n = 16 (43.2%); and 6-NRT, n = 7 (18.9%). Participants with a score ≥ 5 were more likely to have smaller tumors after pre-ET compared with those with a score < 5 (p = 0.04).

CONCLUSIONS

The tumor responses following treatment with pre-ET are heterogenous. We propose that the POWER-PAK scoring system can be used to quantify response to pre-ET. Future studies will explore the use of POWER-PAK to support informed decision-making for adjuvant therapy options for older women with early stage breast cancer.

The quality and clinical translation of radiomics studies based on MRI for predicting Ki-67 levels in patients with breast cancer

OBJECTIVE

To evaluate the methodological quality of radiomics literature predicting Ki-67 levels based on MRI in patients with breast cancer (BC) and to propose suggestions for clinical translation.

METHODS

In this review, we searched PubMed, Embase, and Web of Science for studies published on radiomics in patients with BC. We evaluated the methodological quality of the studies using the Radiomics Quality Score (RQS). The Cochrane Collaboration's software (RevMan 5.4), Meta-DiSc (v. 1.4) and IBM SPSS (v. 26.0) were used for all statistical analyses.

RESULTS

Eighteen studies met our inclusion criteria, and the average RQS was 10.17 (standard deviation [SD]: 3.54). None of these studies incorporated any of the following items: a phantom study on all scanners, cut-off analyses, prospective study, cost-effectiveness analysis, or open science and data. In the meta-analysis, it showed apparent diffusion coefficient (ADC) played a better role to predict Ki-67 level than dynamic contrast-enhanced (DCE) MRI in the radiomics, with the pooled area under the curve (AUC) of 0.969.

CONCLUSION

Ki-67 index is a common tumor biomarker with high clinical value. Radiomics is an ever-growing quantitative data-mining method helping predict tumor biomarkers from medical images. However, the quality of the reviewed studies evaluated by the RQS was not so satisfactory and there are ample opportunities for improvement. Open science and data, external validation, phantom study, publicly open radiomics database and standardization in the radiomics practice are what researchers should pay more attention to in the future.

ADVANCES IN KNOWLEDGE

The RQS tool considered the radiomics used to predict the Ki-67 level was of poor quality. ADC performed better than DCE in radiomic prediction. We propose some measures to facilitate the clinical translation of radiomics.

Machine learning for predicting breast-conserving surgery candidates after neoadjuvant chemotherapy based on DCE-MRI

Purpose

This study aimed to investigate a machine learning method for predicting breast-conserving surgery (BCS) candidates, from patients who received neoadjuvant chemotherapy (NAC) by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) obtained before and after NAC.

Materials and methods

This retrospective study included 75 patients who underwent NAC and breast surgery. First, 3,390 features were comprehensively extracted from pre- and post-NAC DCE-MRIs. Then patients were then divided into two groups: type 1, patients with pathologic complete response (pCR) and single lesion shrinkage; type 2, major residual lesion with satellite foci, multifocal residual, stable disease (SD), and progressive disease (PD). The logistic regression (LR) was used to build prediction models to identify the two groups. Prediction performance was assessed using the area under the curve (AUC), accuracy, sensitivity, and specificity.

Results

Radiomics features were significantly related to breast cancer shrinkage after NAC. The combination model achieved an AUC of 0.82, and the pre-NAC model was 0.64, the post-NAC model was 0.70, and the pre-post-NAC model was 0.80. In the combination model, 15 features, including nine wavelet-based features, four Laplacian-of-Gauss (LoG) features, and two original features, were filtered. Among these selected were four features from pre-NAC DCE-MRI, six were from post-NAC DCE-MRI, and five were from pre-post-NAC features.

Conclusion

The model combined with pre- and post-NAC DCE-MRI can effectively predict candidates to undergo BCS and provide AI-based decision support for clinicians with ensured safety. High-order (LoG- and wavelet-based) features play an important role in our machine learning model. The features from pre-post-NAC DCE-MRI had better predictive performance.

"Diagnostic and Prognostic Biomarkers of Luminal Breast Cancer: Where are We Now?"

Luminal breast cancers are hormone receptor (estrogen and/or progesterone) positive that are further divided into HER2-negative luminal A and HER2-positive luminal B subtypes. According to currently accepted convention, they represent the most common subtypes of breast cancer, accounting for approximately 70% of cases. Biomarkers play a critical role in the functional characterization, prognostication, and therapeutic prediction, rendering them indispensable for the clinical management of invasive breast cancer. Traditional biomarkers include clinicopathological parameters, which are increasingly extended by genetic and other molecular markers, enabling the comprehensive characterization of patients with luminal breast cancer. Liquid biopsies capturing and analyzing circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are emerging technologies that envision personalized management through precision oncology. This article reviews key biomarkers in luminal breast cancer and ongoing developments.

Multiparametric MRI radiomics in prostate cancer for predicting Ki-67 expression and Gleason score: a multicenter retrospective study

PURPOSE

Prostate cancer (PCa) with high Ki-67 expression and high Gleason Scores (GS) tends to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures.

METHODS AND MATERIALS

We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan-Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival.

RESULT

The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI 0.681,0.930) and 0.793 (95% CI 0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified using DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS).

CONCLUSIONS

Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision-making.

Calcium-Sensing Receptor Expression in Breast Cancer

The calcium-sensing receptor (CaSR) plays a crucial role in maintaining the balance of calcium in the body. Altered signaling through the CaSR has been linked to the development of various tumors, such as colorectal and breast tumors. This retrospective study enrolled 79 patients who underwent surgical removal of invasive breast carcinoma of no special type (NST) to explore the expression of the CaSR in breast cancer. The patients were categorized based on age, tumor size, hormone receptor status, HER2 status, Ki-67 proliferation index, tumor grade, and TNM staging. Immunohistochemistry was conducted on core needle biopsy samples to assess CaSR expression. The results revealed a positive correlation between CaSR expression and tumor size, regardless of the tumor surrogate subtype (p = 0.001). The expression of ER exhibited a negative correlation with CaSR expression (p = 0.033). In contrast, a positive correlation was observed between CaSR expression and the presence of HER2 receptors (p = 0.002). Increased CaSR expression was significantly associated with lymph node involvement and the presence of distant metastasis (p = 0.001 and p = 0.038, respectively). CaSR values were significantly higher in the patients with increased Ki-67 (p = 0.042). Collectively, higher CaSR expression in breast cancer could suggest a poor prognosis and treatment outcome regardless of the breast cancer subtype.

Molecular profiling of aromatase inhibitor sensitive and resistant ER+HER2- postmenopausal breast cancers

Aromatase inhibitors (AIs) reduce recurrences and mortality in postmenopausal patients with oestrogen receptor positive (ER+) breast cancer (BC), but >20% of patients will eventually relapse. Given the limited understanding of intrinsic resistance in these tumours, here we conduct a large-scale molecular analysis to identify features that impact on the response of ER + HER2- BC to AI. We compare the 15% of poorest responders (PRs, n = 177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant AI to good responders (GRs, n = 190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In this work, low ESR1 levels are associated with poor response, high proliferation, high expression of growth factor pathways and non-luminal subtypes. PRs having high ESR1 expression have similar proportions of luminal subtypes to GRs but lower plasma estradiol levels, lower expression of estrogen response genes, higher levels of tumor infiltrating lymphocytes and immune markers, and more TP53 mutations.

Comparison of Clinical Outcomes, Pathologic Characteristics, and Immune-Related Features of Postradiation vs Sporadic Oral Cavity Squamous Cell Carcinoma

Importance

Postradiation oral cavity squamous cell carcinoma (OCSCC) is a common secondary malignant neoplasm affecting survivors of head and neck cancer who underwent radiotherapy. The clinical, pathologic, and immune-related features of postradiation OCSCC are poorly characterized, and treatment options are limited because of surgical difficulty and high morbidity associated with reirradiation.

Objective

To determine whether postradiation OCSCC has distinctive clinical, pathologic, and immune-related features compared with demographic-matched sporadic OCSCC.

Design, Setting, and Participants

This retrospective matched cohort study was conducted at a single tertiary oncology center in Hong Kong. Participants included consecutive patients with OCSCC diagnosed between 2000 and 2020. Patients with postradiation OCSCC were matched with patients with sporadic OCSCC using age, year of diagnosis, sex, and anatomic subsites. Data analysis was performed from July to December 2022.

Exposure

Head and neck irradiation involving the oral cavity before the diagnosis of OCSCC.

Main Outcomes and Measures

The primary outcomes were relapse pattern, survival, and causes of death. Pathologic features; immunohistochemical staining for programmed death-ligand 1, PD-1, MSH6, PMS2, FOXP3, and Ki67; and mRNA expression of 31 immune-related genes were also analyzed.

Results

A total of 173 patients, 60 with postradiation OCSCC (median [IQR] age, 63.8 [53.0-71.7] years; 43 men [71.7%]) and 113 with sporadic OCSCC (median [IQR] age, 64.4 [52.8-70.6] years; 83 men [73.5%]), were included. Patients with postradiation OCSCC had a higher proportion of N0 disease than those with sporadic OCSCC (50 patients [83.3%] vs 56 patients [49.6%]). With a median (IQR) follow-up of 10.2 (1.2-20.5) years, the 10-year relapse-free survival rates were lower in patients with postradiation OCSCC than sporadic OCSCC (29.6% [95% CI, 17.1%-43.2%] vs 52.4% [95% CI, 41.8%-62.0%]; P = .04), and the same was true for overall survival (30.5% [95% CI, 17.6%-44.4%] vs 52.3% [95% CI, 41.4%-62.1%]; P = .03). All relapses in patients with postradiation OCSCC were locoregional, whereas 35.2% of relapses (12 of 34 patients) in patients with sporadic OCSCC were distant. Despite similar 10-year disease-specific survival rates between the 2 groups (68.8% [95% CI, 55.8%-81.0%] vs 67.1% [95% CI, 57.5%-76.5%]; P = .91), patients with postradiation OCSCC had excess mortality due to pneumonia and cerebrovascular events. Postradiation OCSCC exhibited more adverse pathologic features (perineural invasion, worse pattern of invasion, and tumor budding), higher PD-1 expression, and higher gene expression of CD4 and TGF-β compared with sporadic OCSCC.

Conclusions and Relevance

This retrospective matched cohort study found distinctive pathologic characteristics and relapse patterns of postradiation OCSCC compared with sporadic OCSCC, which may be attributable to the lack of adjuvant radiotherapy, aggressive biologic phenotype, and different host immune response. Further exploration of the role of immune checkpoint therapy may be justified.

Geniposide prevents tumor growth by inhibiting colonic interleukin-1β and monocyte chemoattractant protein-1 via down-regulated expression of cyclooxygenase-2 and thymocyte selection-associated high mobility box proteins TOX/TOX2 in azoxymethane/dextran sulfate sodium-treated mice

Colon cancer was the second leading cause of cancer-related deaths in Japan in 2019. The effects of geniposide isolated from Gardenia jasminoides fructus (Rubiaceae) on the azoxymethane (AOM)/dextran sulfate sodium (DSS)-induced growth of colon tumors and changes in interleukin (IL)-1 β, monocyte chemoattractant protein (MCP)-1, IL-10, and programmed cell death-1 (PD-1) levels in the colon were investigated. The intraperitoneal administration of AOM (10 mg/kg) on days 0 and 27 induced colorectal carcinogenesis. Free access to 1% (w/v) DSS drinking water was given to mice on days 7-15, 32-33, and 35-38. Geniposide (30 and 100 mg/kg) was orally administered on days 1-16, discontinued for 11 days (days 16 to 26), and then administered again on days 27-41. Colonic levels of cytokines, chemokine, and PD-1 were measured using by enzyme-linked immunosorbent assay (ELISA). Increases in colorectal tumor numbers and areas were significantly inhibited by geniposide. In addition, geniposide (100 mg/kg) reduced colonic levels of IL-1 β, MCP-1, PD-1 and IL-10 by 67.4, 57.2, 100%, and 100% respectively. Cyclooxygenase (COX)-2- and thymocyte selection high mobility group box proteins (TOX/TOX2)-positive cell numbers were significantly reduced by geniposide. Geniposide (30 and 100 mg/kg) decreased the phosphorylation of signal transducer and activator of transcription 3 (STAT3) expressions in immunohistochemical analysis by 64.2 and 98.2%, respectively. Thus, the inhibitory effects of geniposide on colon tumor growth may be associated with reductions in the colonic levels of IL-1 β, MCP-1, IL-10, and PD-1 via the down-regulated expression of COX-2 and TOX/TOX2 through the inhibition of Phospho-STAT3 expression (in vivo and in vitro).

TAF1D promotes proliferation by transcriptionally activating G2/M phase-related genes in MYCN-amplified neuroblastoma

High-risk neuroblastoma (HR-NB) is an aggressive childhood cancer that responds poorly to currently available therapies and is associated with only about a 50% 5-year survival rate. MYCN amplification is a critical driver of these aggressive tumors, but so far there have not been any approved treatments to effectively treat HR-NB by targeting MYCN or its downstream effectors. Thus, the identification of novel molecular targets and therapeutic strategies to treat children diagnosed with HR-NB represents an urgent unmet medical need. Here, we conducted a targeted siRNA screening and identified TATA box-binding protein-associated factor RNA polymerase I subunit D, TAF1D, as a critical regulator of the cell cycle and proliferation in HR-NB cells. Analysis of three independent primary NB cohorts determined that high TAF1D expression correlated with MYCN-amplified, high-risk disease and poor clinical outcomes. TAF1D knockdown more robustly inhibited cell proliferation in MYCN-amplified NB cells compared with MYCN-non-amplified NB cells, as well as suppressed colony formation and inhibited tumor growth in a xenograft mouse model of MYCN-amplified NB. RNA-seq analysis revealed that TAF1D knockdown downregulates the expression of genes associated with the G2/M transition, including the master cell-cycle regulator, cell-cycle-dependent kinase 1 (CDK1), resulting in cell-cycle arrest at G2/M. Our findings demonstrate that TAF1D is a key oncogenic regulator of MYCN-amplified HR-NB and suggest that therapeutic targeting of TAF1D may be a viable strategy to treat HR-NB patients by blocking cell-cycle progression and the proliferation of tumor cells.

Clinico-pathologic relationships with Ki67 and its change with short-term aromatase inhibitor treatment in primary ER + breast cancer: further results from the POETIC trial (CRUK/07/015)

PURPOSE

Ki67 assessed at diagnosis (Ki67baseline) is an important prognostic factor in primary oestrogen receptor-positive (ER +) breast cancer. Proportional change in Ki67 after 2 weeks (∆Ki672week) is associated with clinical benefit from endocrine therapies and residual Ki67 (Ki672week) with recurrence-free survival. The aim was to define the association between Ki67baseline and after aromatase inhibitor (AI) exposure ∆Ki672week and Ki672week with key prognostic and biologic factors utilising data from the POETIC study.

PATIENTS AND METHODS

In POETIC 4480 postmenopausal patients with primary ER and/or PgR + breast cancer were randomised 2:1 to 2 weeks' presurgical AI (anastrozole or letrozole) or no presurgical treatment (control). Ki67 was measured centrally in core-cut biopsies taken prior to AI and in core-cuts or the excision biopsy at surgery. Relationships between the Ki67 and biologic factors were explored using linear regression.

RESULTS

Established associations of Ki67baseline with biologic factors including PgR status, tumour grade, tumour size, histological subtype, nodal status, and vascular invasion were confirmed in the HER2- subpopulation. In the HER2 + subpopulation only grade and tumour size were significantly associated with Ki67baseline. In control group Ki672week was 18% lower than Ki67baseline (p < 0.001) when Ki672week was measured in excision biopsies but not when measured in core-cuts. Median suppression by AIs (∆Ki672week) was 79.3% (IQR: -89.9 to -54.6) and 53.7% (IQR: -78.9 to -21.1) for HER2-negative and HER2-positive cases, respectively. Significantly less suppression occurred in PgR- vs PgR + and HER2 + vs HER2- tumours which remained apparent after adjustment for 2-week sample type.

CONCLUSIONS

The magnitude of this study allowed characterisation of relationships between Ki67baseline, ∆Ki672week and Ki672week with high degrees of confidence providing a reference source for other studies. Lower values of Ki67 occur when measured on excision biopsies and could lead to apparent but artefactual decreases in Ki67: this should be considered when either ∆Ki672week or Ki672week is used in routine clinical practice to aid treatment decisions or in clinical trials assessing new drug therapies.

Physics-based tissue simulator to model multicellular systems: A study of liver regeneration and hepatocellular carcinoma recurrence

We present a multiagent-based model that captures the interactions between different types of cells with their microenvironment, and enables the analysis of the emergent global behavior during tissue regeneration and tumor development. Using this model, we are able to reproduce the temporal dynamics of regular healthy cells and cancer cells, as well as the evolution of their three-dimensional spatial distributions. By tuning the system with the characteristics of the individual patients, our model reproduces a variety of spatial patterns of tissue regeneration and tumor growth, resembling those found in clinical imaging or biopsies. In order to calibrate and validate our model we study the process of liver regeneration after surgical hepatectomy in different degrees. In the clinical context, our model is able to predict the recurrence of a hepatocellular carcinoma after a 70% partial hepatectomy. The outcomes of our simulations are in agreement with experimental and clinical observations. By fitting the model parameters to specific patient factors, it might well become a useful platform for hypotheses testing in treatments protocols.

Acertannin prevents azoxymethane/dextran sulfate sodium-induced colon cancer growth by inhibiting the colonic expression of interleukin-1β, monocyte chemoattractant protein-1, cyclooxygenase-2, and thymocyte selection-associated high mobility group box proteins (TOX)/TOX2 in C57BL/6J mice

Colon cancer was the second leading cause of cancer-related death in 2019. We herein investigated the effects of acertannin containing Acer species on azoxymethane (AOM)/dextran sulfate sodium (DDS)-induced colon cancer growth and changes in the colonic levels of interleukin (IL)-1β, monocyte chemoattractant protein (MCP)-1, IL-10, and programmed cell death-1 (PD-1). Colorectal carcinogenesis was induced by an intraperitoneal injection of AOM (10 mg/kg) on days 0 and 27. Mice were given 1% (w/v) DSS drinking water ad libitum on days 7-14, 32-33, and 35-38. Acertannin (30 and 100 mg/kg) was orally administered on days 1-16, discontinued for 11 days (days 16-26), and then administered again on days 27-41. The colonic levels of cytokines, a chemokine, and PD-1 were measured using the respective ELISA kits. The number and area of tumors in mice treated with acertannin (100 mg/kg) decreased by 53.9 and 63.1%, respectively. Furthermore, the colonic levels of IL-1β, MCP-1, IL-10, and PD-1 showed reductions of 57.3, 62.9, 62.8, and 100%, respectively, while the numbers of cyclooxygenase-2 (COX-2)-, thymocyte selection-associated high mobility group box proteins (TOX)/TOX2-, PD-1-, and signal transducer and activator of transcription 3 (STAT3) phosphorylation-positive numbers decreased by 79.6, 77.9, 93.8, and 100%, respectively. In conclusion, the inhibitory effects of acertannin on AOM/DSS-induced colon tumor growth appear to be associated with reductions in the colonic levels of IL-1β, MCP-1, IL-10, and PD-1 through the down-regulated expression of COX-2 and TOX/TOX2 in the tumor microenvironment.

Clinical correlation analysis of HPV infection in adult laryngeal papilloma and adverse events

OBJECT

To explore the factors affecting dysplasia and carcinogenesis in adult patients with laryngeal papilloma, and the clinical differences between human papillomavirus (HPV)-positive and HPV-negative patients.

METHODS

Clinical data of 80 adult patients with laryngeal papilloma and associated adverse events were collected retrospectively. They had undergone surgery in the Department of Otolaryngology Head and Neck, Beijing Tongren Hospital, Capital Medical University between January 2010 and December 2020. HPV infection was detected using RNA in situ hybridization.

RESULTS

Regression analysis showed that multiple lesions and high Ki-67 expression were independent factors affecting the occurrence of adverse events. Differences between the HPV-positive and HPV-negative groups were compared. The age and Ki-67 expression in the HPV-negative group were significantly higher than those in the HPV-positive group. In the severe dysplasia to carcinogenesis subgroup, the proportion of HPV-negative patients was significantly higher than that in the mild to moderate dysplasia subgroup. There was a high correlation between positive p16 immunohistochemistry (IHC) and positive HPV.

CONCLUSIONS

Multiple lesions and high Ki-67 expression are independent factors that are linked with adverse laryngeal papilloma progression. Elderly HPV-negative patients are at an increased risk of severe dysplasia and carcinogenesis. Positive p16 IHC was very accurate in detecting HPV infection.

Palmitic acid-modified human serum albumin paclitaxel nanoparticles targeting tumor and macrophages against breast cancer

Breast cancer is the most common malignant tumor in women, and the liver is the main target organ for breast cancer metastasis. Once metastasis occurs, the prognosis is very poor. The uptake of PSA NPs made by our synthesized Palmitic acid-modified human serum albumin (PSA) in macrophages is about 15 times higher than that of HSA NPs. As a first-line chemotherapeutic drug, paclitaxel not only does not kill macrophages, but it can also polarize macrophages into classically activated macrophages (M1). We combined these two characteristics into PTX-PSA NPs, which achieved dual targeting of macrophages and tumor cells, improved the tumor microenvironment, and achieved a more effective anti-breast cancer drug effect than PTX-HSA NPs. On this basis, we also used the pathological characteristics of low vascular perfusion of breast cancer liver metastasis, and used the characteristics of macrophages that can release paclitaxel after internalizing paclitaxel, and use macrophages as the delivery system of breast cancer liver metastasis. Therefore,PTX-PSA NPs is better than PTX-HSA NPs to achieve anti-breast cancer liver metastasis.

Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram

PURPOSE

The objective of this research was to develop and validate an ultrasound-based radiomics nomogram for the pre-operative assessment of Ki-67 in breast cancer (BC).

MATERIALS AND METHODS

From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two-dimensional (2D) ultrasound and Ki-67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki-67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.

RESULTS

In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690-0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility.

CONCLUSIONS

The nomogram based on 2D ultrasound images offered an approach for predicting Ki-67 in BC.

A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 antigen are the most examined markers depicting BC heterogeneity and have been shown to have a strong impact on BC prognosis. Radiomics can noninvasively predict BC heterogeneity through the quantitative evaluation of medical images, such as Magnetic Resonance Imaging (MRI), which has become increasingly important in the detection and characterization of BC. However, the lack of comprehensive BC datasets in terms of molecular outcomes and MRI modalities, and the absence of a general methodology to build and compare feature selection approaches and predictive models, limit the routine use of radiomics in the BC clinical practice. In this work, a new radiomic approach based on a two-step feature selection process was proposed to build predictors for ER, PR, HER2, and Ki67 markers. An in-house dataset was used, containing 92 multiparametric MRIs of patients with histologically proven BC and all four relevant biomarkers available. Thousands of radiomic features were extracted from post-contrast and subtracted Dynamic Contrast-Enanched (DCE) MRI images, Apparent Diffusion Coefficient (ADC) maps, and T2-weighted (T2) images. The two-step feature selection approach was used to identify significant radiomic features properly and then to build the final prediction models. They showed remarkable results in terms of F1-score for all the biomarkers: 84%, 63%, 90%, and 72% for ER, HER2, Ki67, and PR, respectively. When possible, the models were validated on the TCGA/TCIA Breast Cancer dataset, returning promising results (F1-score = 88% for the ER+/ER- classification task). The developed approach efficiently characterized BC heterogeneity according to the examined molecular biomarkers.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Marker assessments in ER-positive breast cancers: old markers, new applications?

Evaluation of oestrogen receptor (ER) expression by immunostaining is essential in the pathological assessment of breast cancer. Its expression is intercorrelated with clinicopathological features, molecular typing, and treatment selection. The development of novel therapeutic agents related to ER status, the recent ASCO introduction of an ER-low positive category of breast cancers, and the ever-increasing plethora of diagnostic and theragnostic markers call for a timely update. In this article we aim to review the clinicopathological features of ER-positive breast cancers, with an emphasis on ER-low positive breast cancers, and a focus on updating the (i) assessment, reporting and interpretation of ER immunohistochemical (IHC) staining, (ii) correlations of ER status with other diagnostic and theragnostic markers, and (iii) implications for treatment selection and response. In the face of the developments in IHC and molecular techniques and targeted therapy, ER immunostaining is still expected to remain as the core component of prognostic and theragnostic assessment of breast cancers.

The complex nature of heterogeneity and its roles in breast cancer biology and therapeutic responsiveness

Heterogeneity is a complex feature of cells and tissues with many interacting components. Depending on the nature of the research context, interacting features of cellular, drug response, genetic, molecular, spatial, temporal, and vascular heterogeneity may be present. We describe the various forms of heterogeneity with examples of their interactions and how they play a role in affecting cellular phenotype and drug responses in breast cancer. While cellular heterogeneity may be the most widely described and invoked, many forms of heterogeneity are evident within the tumor microenvironment and affect responses to the endocrine and cytotoxic drugs widely used in standard clinical care. Drug response heterogeneity is a critical determinant of clinical response and curative potential and also is multifaceted when encountered. The interactive nature of some forms of heterogeneity is readily apparent. For example, the process of metastasis has the properties of both temporal and spatial heterogeneity within the host, whereas each individual metastatic deposit may exhibit cellular, genetic, molecular, and vascular heterogeneity. This review describes the many forms of heterogeneity, their integrated activities, and offers some insights into how heterogeneity may be understood and studied in the future.

Establishment and characterization of a new Chinese hepatocellular carcinoma cell line, Hep-X1

Hepatocellular carcinoma (HCC) is a highly aggressive and heterogeneous disease. Cell lines are commonly employed as in vitro models for cell type studies. However, the success rate of HCC primary culture establishment is low. In this study, we successfully established a liver cancer cell line, Hep-X1. Primary culture and passage of surgically removed tissues were used to establish hepatoma cell lines. Morphological examination, short tandem repeat (STR) analysis, immunohistochemical staining, doubling time, karyotype analysis, plate tumor formation experiments, organoid culture, and in vivo tumor formation investigations in animals were used to identify the cell lines. A novel liver cancer cell line, Hep-X1, was established based on morphology, immunophenotype, cytogenetics, and STR analysis. The novel cell line can be a valuable model for studying primary liver cancer.

The relationships of OSBPL3 expression with KI-67 expression and KRAS mutations in CRC: implications for diagnosis and prognosis

BACKGROUND

OSBPL3 is overexpressed in a variety of malignancies and is closely associated with tumor growth and metastasis. However, its expression and function in colorectal cancer (CRC) are unclear. We aimed to investigate its prognostic and therapeutic value in this disease by detecting its expression in CRC and its correlation with the clinicopathological characteristics and prognosis of patients.

METHODS

A total of 92 CRC samples were included in this study. According to the 2020 WHO diagnostic criteria, the criteria of the American Joint Committee on Cancer (AJCC) 8th edition staging system were used. OSBPL3 and Ki-67 expression in these samples was detected by immunohistochemistry. OSBPL3 mRNA expression was detected by qRT-PCR. KRAS/NRAS mutations were detected by an amplification refractory mutation system (ARMS). Data analysis was performed using the statistical analysis software Prism 8.

RESULTS

OSBPL3 was found to be significantly overexpressed in CRC tumor tissues and was associated with worse progression-free survival and overall survival in patients. Additionally, OSBPL3 expression was negatively correlated with the degree of tumor differentiation. KRAS mutations were detected in approximately 32.6% of patients and were significantly associated with high OSBPL3 expression. In addition, OSBPL3 and Ki-67 expression was significantly correlated.

CONCLUSIONS

OSBPL3 is highly expressed in CRC samples and predicts a worse prognosis. OSBPL3 may become a new potential therapeutic target for CRC.

High SURF4 expression is associated with poor prognosis of breast cancer

SURF4 has been suggested as an oncogene in cancer. However, the role of SURF4 in breast cancer has not been demonstrated yet. The data were obtained from TCGA database and 1104 patients were analyzed using bioinformatics analysis. SURF4 is significantly (P < 0.001) highly expressed in tumor. High expression of SURF4 was observed in T4, infiltrating ductal carcinoma, ER negative, PR negative, and HER2 positive, female, patients without lymph node metastasis, HER2 overexpression type, and deceased patients. As for characteristics correlated with high expression of SURF4, gender, histological type, molecular subtype, ER, PR, HER2, and vital status exhibited significant differences. The age (HR: 2.317, P < 0.001), stage (HR: 2.090, P < 0.001), and SURF4 expression (HR: 1.958, P = 0.005) exhibited independent prognostic value for overall survival (OS). Patients with high SURF4 expression, higher age, equivocal HER2, higher stages, or positive margin status had shorter OS. The stage (HR: 1.579, P < 0.001), and margin status (HR: 1.463, P = 0.006) exhibited independent prognostic value for relapse-free survival of breast cancer. High expression of SURF4 was first found in breast cancer. High SURF4 expression was observed in breast cancer tissue and cell. SURF4 promoted the proliferation and migration of 4T1 cells. SURF4 may be a biomarker in diagnosis and prognosis of breast cancer.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning

Background and Objective. Breast cancer is a common malignant tumor that seriously threatens the health of women in my country and even around the world. The proliferation marker Ki-67 has been utilized to distinguish luminal B from luminal A tumors and is a reliable indicator of more aggressive breast cancer growth. If a reliable prediction method for breast cancer patients to avoid invasive damage can be found to predict Ki-67 before pathological examination, it will be very beneficial for doctors to formulate later treatment plans and provide more useful treatment options. Methodology. This paper proposes a tumor segmentation and prediction framework based on the combination of improved attention U-Net and SVM. The framework first improves on attention U-Net by introducing coefficients for learning multidimensional attention. Make the attention mechanism more aware of the main situation in the segmentation process. At the same time, the segmented breast MRI results and corresponding labels were input into the SVM classifier to accurately predict the expression of Ki-67. Results. The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion. Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.

Slow degrading Mg-based materials induce tumor cell dormancy on an osteosarcoma-fibroblast coculture model

Osteosarcoma is one of the most common cancers in young adults and is commonly treated using surgery and chemotherapy. During the past years, these therapy approaches improved but failed to ameliorate the outcomes. Therefore, novel, targeted therapeutic approaches should be established to enhance treatment success while preserving patient's quality of life. Recent studies suggest the application of degradable magnesium (Mg) alloys as orthopedic implants bearing a potential antitumor activity. Here, we examined the influence of Mg-based materials on an osteosarcoma-fibroblast coculture. Both, Mg and Mg-6Ag did not lead to tumor cell apoptosis at low degradation rates. Instead, the Mg-based materials induced cellular dormancy in the cancer cells indicated by a lower number of Ki-67 positive cancer cells and a higher p38 expression. This dormancy-like state could be reversed by reseeding on non-degrading glass slides but could not be provoked by inhibition of the protein kinase R-like endoplasmic reticulum kinase. By investigating the influence of the disjunct surface-near effects of the Mg degradation on cell proliferation, an increased pH was found to be a main initiator of Mg degradation-dependent tumor cell proliferation inhibition.

Olive Leaf Extract Attenuates Chlorpyrifos-Induced Neuro- and Reproductive Toxicity in Male Albino Rats

Chlorpyrifos (CPF) is a common organophosphorus insecticide. It is associated with negative consequences such as neurotoxicity and reproductive injury. This study aimed to observe the ability of olive leaf extract to attenuate chlorpyrifos toxicity, which induced neuro- and reproductive toxicity in male albino rats. Olive leaf extract (OLE) exhibits potent antioxidant and antiapoptotic properties. Twenty-two mature male rats were divided into four groups: control (saline), CPF (9 mg/kg), OLE (150 mg/kg), and CPF + OLE. Treatment was administered orally for 80 days. The CPF significantly reduced serum sex hormones, sperm counts and motility, high oxidants (MDA), and depleted antioxidants (GSH, SOD, TAC) in the brain and testes homogenate; additionally, it decreased serum AChE and brain neurotransmitters, increased Bax, decreased Bcl-2, and boosted caspase-3 immune expression in neural and testicular cells. Immunological expression of Ki 67 in the cerebrum, cerebellum, choroid plexus, and hippocampus was reduced, and α-SMA in testicular tissue also decreased. Histopathological findings were consistent with the above impacts. OLE co-administration significantly normalized all these abnormalities. OLE showed significant protection against neural and reproductive damage caused by CPF.

Update Breast Cancer 2022 Part 3 - Early-Stage Breast Cancer

This review summarizes recent developments in the prevention and treatment of patients with early-stage breast cancer. The individual disease risk for different molecular subtypes was investigated in a large epidemiological study. With regard to treatment, new data are available from long-term follow-up of the Aphinity study, as well as new data on neoadjuvant therapy with atezolizumab in HER2-positive patients. Biomarkers, such as residual cancer burden, were investigated in the context of pembrolizumab therapy. A Genomic Grade Index study in elderly patients is one of a group of studies investigating the use of modern multigene tests to identify patients with an excellent prognosis in whom chemotherapy may be avoided. These and other aspects of the latest developments in the diagnosis and treatment of breast cancer are described in this review.

Ki-67 Index Provides Long-Term Survival Information for Early-Stage HER2-Low-Positive Breast Cancer: A Single-Institute Retrospective Analysis

Aim

It has been reported that more than half of breast cancer (BC) could be identified as HER2-low-positive, which might be a distinct subtype. But the results are controversial. We aim to compare the survival outcomes between HER2-low-positive and HER2-0 BC with Asian women based on HR status or Ki-67 index.

Methods

Between January 2009 and December 2017, HER2-nonamplified BC in our single institute was identified. Patients were classified as HER2-low and HER2-0 cohort. Clinical characteristics were compared between these two groups and survival outcomes were calculated by the Kaplan–Meier method. We also performed subgroup analysis according to Ki-67 index and hormone-receptor (HR) status.

Results

Of the 2,230 included patients, 536 presented with HER2-0, and 1,694 with HER2-low positive. After a median follow-up of 85 months (range: 1–152 months), the 8-year OS, BCSS, and RFS of the overall cohort were 91%, 95%, and 89%, respectively. In comparison with the HER2-0 cohort, majority of HER2-low-expression BC concurrently presented with HR positive (82.3% vs. 69%, P < 0.001). There was no significant survival difference between the two groups in terms of OS, BCSS, and RFS (all p > 0.05). We then performed subgroup analysis according to HR status and Ki-67 index (<14% vs. ≥14%). Our results indicated that there was no significant survival difference between HER2-low-positive and HER2-0 tumors regardless of HR status (p > 0.05), while OS (p=0.026) and BCSS (p=0.052) of HER2-0 BC with high Ki-67 index were significantly poorer than that of HER2-low positive with high Ki-67, but not for RFS (p=0.17).

Conclusion

Among early stage HER2-nonamplified BC, no significant survival difference could be found between HER2-low positive and HER2-0 cohort regardless of HR status. Survival outcomes of HER2-low positive with high Ki-67 seem to be poorer than that of HER2-0 tumors with high Ki-67 index.

♣Evaluation of clinicopathological profiles and development of a risk model in renal epithelioid angiomyolipoma patients: a large-scale retrospective cohort study

BACKGROUND

To identify the malignant potential and prognostic indicators of renal epithelioid angiomyolipoma (eAML), clinicopathological and molecular features as well as the drug efficacy of 67 eAML cases were analyzed.

MATERIALS AND METHODS

Sixty-seven renal eAML patients were enrolled and the immunohistochemical features of these patients were examined. FFPE slides of all patients were re-examined. 21 patients with metastasis received Everolimus 10 mg orally once daily. Responses were evaluated with RECIST criteria by three authors. A risk stratification model was constructed using the following factors: pT3 and pT4, presence of necrosis, mitotic count ≥ 2; the presence of atypical mitoses; severe nuclear atypia, SMA negative, Ki-67 ≥ 10%.

RESULTS

The average percentage of the epithelioid component was 85.6% (range 80-95%). Immunohistochemically, Ki-67 ≥ 10% and negative SMA staining were significantly correlated with malignant characteristics (Ki-67: p < 0.001; SMA: p = 0.001). Survival analysis suggested that pT3-pT4 stage, presence of necrosis, severe nuclear atypia, presence of atypical mitoses, mitotic count ≥ 2, Ki-67 ≥ 10% and negative SMA expression were significantly associated with poorer PFS and OS (p < 0.05). The risk model sufficiently discriminated recurrence/metastasis (AUC = 0.897) and cancer-specific mortality (AUC = 0.932) of renal eAML patients in different risk groups. 21 patients had received Everolimus targeted therapy after recurrence/metastasis. The best response for Everolimus treatment was 8/21 (38.1%) partial responses (PR), 9/21 (42.9%) stable disease (SD) and 4/21 (19.0%) progressive disease (PD).

CONCLUSION

The risk stratification model could well distinguish eAML patients at high risk of recurrence/metastasis. Everolimus targeted treatment showed good efficacy in patients with recurrence/metastasis.

Development of an ultrasound-based radiomics nomogram to preoperatively predict Ki-67 expression level in patients with breast cancer

Objective

To develop and validate a radiomics nomogram that could incorporate clinicopathological characteristics and ultrasound (US)-based radiomics signature to non-invasively predict Ki-67 expression level in patients with breast cancer (BC) preoperatively.

Methods

A total of 328 breast lesions from 324 patients with BC who were pathologically confirmed in our hospital from June 2019 to October 2020 were included, and they were divided into high Ki-67 expression level group and low Ki-67 expression level group. Routine US and shear wave elastography (SWE) were performed for each lesion, and the ipsilateral axillary lymph nodes (ALNs) were scanned for abnormal changes. The datasets were randomly divided into training and validation cohorts with a ratio of 7:3. Correlation analysis and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomics features obtained from gray-scale US images of BC patients, and each radiomics score (Rad-score) was calculated. Afterwards, multivariate logistic regression analysis was used to establish a radiomics nomogram based on the radiomics signature and clinicopathological characteristics. The prediction performance of the nomogram was assessed by the area under the receiver operating characteristic curve (AUC), the calibration curve, and decision curve analysis (DCA) using the results of immunohistochemistry as the gold standard.

Results

The radiomics signature, consisted of eight selected radiomics features, achieved a nearly moderate prediction efficacy with AUC of 0.821 (95% CI:0.764-0.880) and 0.713 (95% CI:0.612-0.814) in the training and validation cohorts, respectively. The radiomics nomogram, incorporating maximum diameter of lesions, stiff rim sign, US-reported ALN status, and radiomics signature showed a promising performance for prediction of Ki-67 expression level, with AUC of 0.904 (95% CI:0.860-0.948) and 0.890 (95% CI:0.817-0.964) in the training and validation cohorts, respectively. The calibration curve and DCA indicated promising consistency and clinical applicability.

Conclusion

The proposed US-based radiomics nomogram could be used to non-invasively predict Ki-67 expression level in BC patients preoperatively, and to assist clinicians in making reliable clinical decisions.

Molecularly cleavable bioinks facilitate high-performance digital light processing-based bioprinting of functional volumetric soft tissues

Digital light processing bioprinting favors biofabrication of tissues with improved structural complexity. However, soft-tissue fabrication with this method remains a challenge to balance the physical performances of the bioinks for high-fidelity bioprinting and suitable microenvironments for the encapsulated cells to thrive. Here, we propose a molecular cleavage approach, where hyaluronic acid methacrylate (HAMA) is mixed with gelatin methacryloyl to achieve high-performance bioprinting, followed by selectively enzymatic digestion of HAMA, resulting in tissue-matching mechanical properties without losing the structural complexity and fidelity. Our method allows cellular morphological and functional improvements across multiple bioprinted tissue types featuring a wide range of mechanical stiffness, from the muscles to the brain, the softest organ of the human body. This platform endows us to biofabricate mechanically precisely tunable constructs to meet the biological function requirements of target tissues, potentially paving the way for broad applications in tissue and tissue model engineering.

Improved Prediction of Survival Outcomes Using Residual Cancer Burden in Combination With Ki-67 in Breast Cancer Patients Underwent Neoadjuvant Chemotherapy

We developed a model for improving the prediction of survival outcome using postoperative Ki-67 value in combination with residual cancer burden (RCB) in patients with breast cancer (BC) who underwent neoadjuvant chemotherapy (NAC). We analyzed the data from BC patients who underwent NAC between 2010 and 2019 at Samsung Medical Center and developed our residual proliferative cancer burden (RPCB) model using semi-quantitative Ki-67 value and RCB class. The Cox proportional hazard model was used to develop our RPCB model according to disease free survival (DFS) and overall survival (OS). In total, 1,959 patients were included in this analysis. Of 1,959 patients, 905 patients were excluded due to RCB class 0, and 32 were due to a lack of Ki-67 data. Finally, an RPCB model was developed using data from 1,022 patients. The RPCB score was calculated for DFS and OS outcomes, respectively (RPCB-DFS and RPCB-OS). For further survival analysis, we divided the population into 3 classes according to the RPCB score. In the prediction of DFS, C-indices were 0.751 vs 0.670 and time-dependent areas under the receiver operating characteristic curves (AUCs) at 3-year were 0.740 vs 0.669 for RPCB-DFS and RCB models, respectively. In the prediction of OS, C-indices were 0.819 vs 0.720 and time-dependent AUCs at 3-year were 0.875 vs 0.747 for RPCB-OS and RCB models, respectively. The RPCB model developed using RCB class and semi-quantitative Ki-67 had superior predictive value for DFS and OS compared with that of RCB class. This prediction model could provide the basis to decide risk-stratified treatment plan for BC patients who had residual disease after NAC.

Two hydroxyflavanones isolated from Scutellaria baicalensis roots prevent colitis-associated colon cancer in C57BL/6 J mice by inhibiting programmed cell death-1, interleukin 10, and thymocyte selection-associated high mobility group box proteins TOX/TOX2

BACKGROUND

Colorectal cancer was the second leading cause of mortality in 2019 and the number of new colorectal cancer cases was the highest in 2018 and 2019 in Japan.

PURPOSE

The present study investigated the inhibitory effects of 2(S)-2',5,6',7-tetrahydroxyflavanone and 2 (R), 3(R)-2',3,5,6'-7-pentahydroxyflavanone on the incidence and growth of tumors in azoxymethane (AOM) plus dextran sulfate sodium (DSS)-treated mice.

METHODS

The intraperitoneal administration of AOM (10 mg/kg) on day 0 induced colorectal carcinogenesis. Mice were given free and unlimited access to drinking water containing 1.5% (w/v) DSS on days 5 - 8, 30 - 33, and 56 - 57. They were orally administered tetra- and penta-hydroxyflavanones (10 and 30 mg/kg) for 10, 11, and 14 days followed by discontinuation intervals of 20 and 15 days. Cytokine, chemokine, programmed cell death-1 (PD-1), cyclooxygenase (COX)-2, and thymocyte selection-associated high mobility group box protein (TOX)/TOX2 expression levels were measured using their respective ELISA kits and an immunohistochemical analysis.

RESULTS

The number and area of tumors decreased by 60.6 and 72.9% in mice administered 10 mg/kg tetra- and pentahydroxyflavanones, respectively, with reductions of 95.0 and 87.0% in Ki-67-positive cells, 91.7 and 92.7% in COX-2-postive cells, and 83.1 and 93.8% in TOX/TOX2-positive cells, respectively, in the colon. On the other hand, two tera- and pentahydroxyflavanone had no effect on p53 (a tumor suppressor by cell cycle arrest and apoptosis)-positive cells. The administration of 10 mg/kg tetra- and pentahydroxyflavanones to AOM/DSS-treated mice also resulted in decreases of 59.5 and 42.5% in IL-10 levels and 58.1 and 93.9% in PD-1 levels, respectively, in the colon.

CONCLUSION

The inhibitory effects of tetra- and pentahydroxyflavanones on the growth of colon tumors in AOM/DSS-treated mice appear to be associated with decreases in the colon levels of IL-10 and PD-1 through the down-regulated expression of COX-2 and CD8⁺ T-cell exhaustion by TOX/TOX2 in the tumor microenvironment.