Currently, there is no established guidance on how to process and evaluate resected lung cancer specimens after neoadjuvant therapy in the setting of clinical trials and clinical practice. There is ...also a lack of precise definitions on the degree of pathologic response, including major pathologic response or complete pathologic response. For other cancers such as osteosarcoma and colorectal, breast, and esophageal carcinomas, there have been multiple studies investigating pathologic assessment of the effects of neoadjuvant therapy, including some detailed recommendations on how to handle these specimens. A comprehensive mapping approach to gross and histologic processing of osteosarcomas after induction therapy has been used for over 40 years.
The purpose of this article is to outline detailed recommendations on how to process lung cancer resection specimens and to define pathologic response, including major pathologic response or complete pathologic response after neoadjuvant therapy. A standardized approach is recommended to assess the percentages of (1) viable tumor, (2) necrosis, and (3) stroma (including inflammation and fibrosis) with a total adding up to 100%. This is recommended for all systemic therapies, including chemotherapy, chemoradiation, molecular-targeted therapy, immunotherapy, or any future novel therapies yet to be discovered, whether administered alone or in combination. Specific issues may differ for certain therapies such as immunotherapy, but the grossing process should be similar, and the histologic evaluation should contain these basic elements. Standard pathologic response assessment should allow for comparisons between different therapies and correlations with disease-free survival and overall survival in ongoing and future trials. The International Association for the Study of Lung Cancer has an effort to collect such data from existing and future clinical trials. These recommendations are intended as guidance for clinical trials, although it is hoped they can be viewed as suggestion for good clinical practice outside of clinical trials, to improve consistency of pathologic assessment of treatment response.
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•The review summarizes the traditional genetic, RNA, and protein biomarkers for esophageal cancer neoadjuvant chemoradiation treatment response prediction.•The review elaborated the ...potential immune, tumor microenvironment, and microbiome biomarkers for treatment response prediction.•The review suggested future directions for esophageal cancer neoadjuvant chemoradiotherapy biomarker research.
Neoadjuvant chemoradiotherapy followed by surgery has been established as the standard treatment for locally advanced esophageal cancer. For patients with complete regression after neoadjuvant chemotherapy, active surveillance rather than planned surgery has been proposed as an organ preservation strategy. Reliable biomarkers to predict chemoradiation response is needed. We first summarized the previous reports of biomarkers with the potential to predict the treatment response of esophageal cancer neoadjuvant chemoradiotherapy. These traditional biomarkers are classified into three groups: genetic biomarkers, RNA biomarkers, and protein biomarkers. We then summarized some special types of biomarkers, including metabolites biomarkers, immune and tumor microenvironment biomarkers, and microbiome biomarkers.
Cancer treatment, in particular radiotherapy and chemotherapy, is often hindered by an inherent resistance of cancer cells. Cancer stem cells in particular have previously been shown to be more ...resistant than other cells within a tumor and are thought repopulate the tumour after therapies. Therefore, it is of utmost importance to develop tools and techniques that can be used to study mechanisms of resistance of cancer stem cells as potential treatment targets. Organoids (and cancer-derived organoids), are three-dimensional tissue-resembling cellular clusters derived from tissue or tumor specific stem cells that mimic the in vivo (tumor) characteristics, as well as (tumor) cell heterogeneity. Cancer organoids may further enhance the in vitro and in vivo models that are currently available, improve our understanding of cancer stem cell resistance and can be used to develop novel cancer treatments by improved targeting of cancer stem cells. In this review, we compare organoids with the more traditional laboratory models, such as cell lines and xenografts, and review the literature of the current role of cancer organoids in determining treatment responses.
Breast cancer (BC) is the second most common cause of cancer‐related deaths in women worldwide. The availability of reliable biomarkers of response/resistance to cancer treatments would benefit ...patients and clinicians allowing for a better selection of BC patients most likely to respond to a specific treatment. Phosphatidylinositol 3‐kinase (PI3K) enzymes are involved in numerous cellular‐ functions and processes. The gene encoding for PI3K catalytic subunit p110α is mutated in 20‐40% of BC. We performed a meta‐analysis of the current literature on randomized clinical trials, investigating the role of PIK3CA mutational status as prognostic factor, and predictor of response to anti‐cancer treatments. Overall 1929 cases were included. The pooled analysis confirmed that the presence of a PIK3CA mutation represents an independent negative prognostic factor (HR = 1.67, 95%CI: 1.15‐2.43; P = 0.007) in BC, as previously reported. As PI3K signaling is also a result of other pathways’ hyperactivation, further investigation of potential biomarkers able to predict likelihood of response to anti‐PI3K/mTOR, anti‐HER2, and other TKRs is warranted in future randomized clinical trials.
Breast cancer is the second most common cause of cancer‐related deaths in women. More accurate biomarkers of response to treatment and predictors of prognosis are needed. Phosphatidylinositol 3‐kinase gene is mutated in 20‐40% of BC. In our meta‐analysis PI3K is an independent negative prognostic factor and correlates with a worse prognosis (P = 0.007)
In this meta‐analysis investigating the role of PIK3CA mutations in 1928 breast cancer cases, it was proved that the mutational status of this gene was an independent negative prognostic factor, and correlated with a worse prognosis (HR = 1.67, 95%CI: 1.15‐2.43; P = 0.007).
•Early Identification or Prediction of COVID-19 cases.•Real-time Monitoring of COVID-19.•Treatment Response of COVID-19 confirmed cases.•An IoT-based Framework for COVID-19.
The world has been facing ...the challenge of COVID-19 since the end of 2019. It is expected that the world will need to battle the COVID-19 pandemic with precautious measures, until an effective vaccine is developed. This paper proposes a real-time COVID-19 detection and monitoring system. The proposed system would employ an Internet of Things (IoTs) framework to collect real-time symptom data from users to early identify suspected coronaviruses cases, to monitor the treatment response of those who have already recovered from the virus, and to understand the nature of the virus by collecting and analyzing relevant data. The framework consists of five main components: Symptom Data Collection and Uploading (using wearable sensors), Quarantine/Isolation Center, Data Analysis Center (that uses machine learning algorithms), Health Physicians, and Cloud Infrastructure. To quickly identify potential coronaviruses cases from this real-time symptom data, this work proposes eight machine learning algorithms, namely Support Vector Machine (SVM), Neural Network, Naïve Bayes, K-Nearest Neighbor (K-NN), Decision Table, Decision Stump, OneR, and ZeroR. An experiment was conducted to test these eight algorithms on a real COVID-19 symptom dataset, after selecting the relevant symptoms. The results show that five of these eight algorithms achieved an accuracy of more than 90 %. Based on these results we believe that real-time symptom data would allow these five algorithms to provide effective and accurate identification of potential cases of COVID-19, and the framework would then document the treatment response for each patient who has contracted the virus.
Owing to major advances in the field of radiation oncology, patients with lung cancer can now receive technically individualized radiotherapy treatments. Nevertheless, in the era of precision ...oncology, radiotherapy-based treatment selection needs to be improved as many patients do not benefit or are not offered optimum therapies. Cost-effective robust biomarkers can address this knowledge gap and lead to individuals being offered more bespoke treatments leading to improved outcome. This narrative review discusses some of the current achievements and challenges in the realization of personalized radiotherapy delivery in patients with lung cancer.
Common computed tomography (CT) investigation plays a limited role in characterizing and assessing the response of rectal cancer (RC) to neoadjuvant radiochemotherapy (NARC). Photon counting computed ...tomography (PCCT) improves the imaging quality and can provide multiparametric spectral image information including iodine concentration (IC). Our purpose was to analyze associations between IC and histopathology in RC and to evaluate the role of IC in response prediction to NARC.
Overall, 41 patients were included into the study, 14 women and 27 men, mean age, 65.5 years. PCCT in a portal venous phase of the abdomen was performed. In every case, a polygonal region of interest (ROI) was manually drawn on iodine maps. Normalized IC (NIC) was also calculated. Tumor stage, grade, lymphovascular invasion, circumferential resection margin, and tumor markers were analyzed. Tumor regression grade (absence/presence of tumor cells) after NARC was analyzed. NIC values in groups were compared to Mann–Whitney-U tests. Sensitivity, specificity, and area under the curve values were calculated. Intraclass correlation coefficient (ICC) was calculated.
ICC was 0.93, 95%CI= (0.88; 0.96). Tumors with lymphovascular invasion showed higher NIC values in comparison to those without (p = 0.04). Tumors with response grade 2–4 showed higher pretreatment NIC values in comparison to lesions with response grade 0–1 (p = 0.01). A NIC value of 0.36 and higher can predict response grade 2–4 (sensitivity, 73.9%; specificity, 91.7%; area under the curve, 0.85).
NIC values showed an excellent interreader agreement in RC. NIC can predict treatment response to NARC.
We assessed the potential role of serial circulating tumor DNA (ctDNA) as a biomarker to monitor treatment response to primary systemic therapy (PST) in breast cancer and evaluated the predictive ...value of ctDNA to further identify patients with residual disease.
We prospectively enrolled 208 plasma samples collected at three time points (before PST, after 2 cycles of treatment, before surgery) of 72 patients with stage Ⅱ-III breast cancer. Somatic mutations in plasma samples were identified using a customized 128-gene capture panel with next-generation sequencing. The correlation between early change in ctDNA levels and treatment response or long-term clinical outcomes was assessed.
37 of 72 (51.4%) patients harbored detectable ctDNA alterations at baseline. Patients with complete response showed a larger decrease in ctDNA levels during PST. The median relative change of variant allele fraction (VAF) was −97.4%, −46.7%, and +21.1% for patients who subsequently had a complete response (n = 11), partial response (n = 11), and no response (n = 15) (p = 0.0012), respectively. In addition, the relative change of VAF between the pretreatment and first on-treatment blood draw exhibited the optimal predictive value to tumor response after PST (area under the curve, AUC = 0.7448, p = 0.02). More importantly, early change of ctDNA levels during treatment have significant prognostic value for patients with BC, there was a significant correlation between early decrease of VAF and longer recurrence-free survival compared to those with an VAF increase (HR = 12.54; 95% CI, 2.084 to 75.42, p = 0.0063).
Early changes of ctDNA are strongly correlated with therapeutic efficacy to PST and clinical outcomes in BC patients. The integration of preoperative ctDNA evaluation could help improving the perioperative management for BC patients receiving PST.
•The detection of ctDNA before primary systemic treatment (PST) is associated with more aggressive tumor.•The early decrease of ctDNA during the course of PST is a good pathological complete response marker.•The presence of baseline ctDNA and early decrease of ctDNA can be a robust relapse predictor for locally advanced BC.•The potential of preoperative ctDNA detection for PST response prediction in BC.
To date, few studies have compared effectiveness and survival rates of neoadjuvant chemotherapy combined with immunotherapy (NACI) and conventional neoadjuvant chemoradiotherapy (NCRT) in patients ...with locally advanced esophageal squamous cell carcinoma (ESCC). The present study was conducted to compare therapeutic response and survival between NACI and NCRT.
The study cohort comprised patients with locally advanced ESCC treated with either NACI or NCRT followed by surgery between June 2018 and March 2021. The 2 groups were compared for treatment response, 3-year overall survival (OS), and disease-free survival (DFS). Survival curves were created using the Kaplan-Meier method, differences were compared using the log-rank test, and potential imbalances were corrected for using the inverse probability of treatment weighting (IPTW) method.
Among 202 patients with locally advanced ESCC, 81 received NACI and 121 received conventional NCRT. After IPTW adjustment, the R0 resection rate (85.2% vs 92.3%; P = .227) and the pathologic complete response (pCR) rate (27.5% vs 36.4%; P = .239) were comparable between the 2 groups. Nevertheless, patients who received NACI exhibited both a better 3-year OS rate (91.7% vs 79.8%; P = .032) and a better 3-year DFS rate (87.4% vs 72.8%; P = .039) compared with NCRT recipients.
NACI has R0 resection and pCR rates comparable to those of NCRT and seems to be correlated with better prognosis than NCRT. NACI followed by surgery may be an effective treatment strategy for locally advanced ESCC.
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Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic ...research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.
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