Image enhancement plays an important role in image processing and analysis. Among various enhancement algorithms, Retinex-based algorithms can efficiently enhance details and have been widely adopted. Since Retinex-based algorithms regard illumination removal as a default preference and fail to limit the range of reflectance, the naturalness of non-uniform illumination images cannot be effectively preserved. However, naturalness is essential for image enhancement to achieve pleasing perceptual quality. In order to preserve naturalness while enhancing details, we propose an enhancement algorithm for non-uniform illumination images. In general, this paper makes the following three major contributions. First, a lightness-order-error measure is proposed to access naturalness preservation objectively. Second, a bright-pass filter is proposed to decompose an image into reflectance and illumination, which, respectively, determine the details and the naturalness of the image. Third, we propose a bi-log transformation, which is utilized to map the illumination to make a balance between details and naturalness. Experimental results demonstrate that the proposed algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images.

Circulating tumor cells (CTCs) enter peripheral blood from primary tumors and seed metastases. The genome sequencing of CTCs could offer noninvasive prognosis or even diagnosis, but has been hampered by low single-cell genome coverage of scarce CTCs. Here, we report the use of the recently developed multiple annealing and looping-based amplification cycles for whole-genome amplification of single CTCs from lung cancer patients. We observed characteristic cancer-associated single-nucleotide variations and insertions/deletions in exomes of CTCs. These mutations provided information needed for individualized therapy, such as drug resistance and phenotypic transition, but were heterogeneous from cell to cell. In contrast, every CTC from an individual patient, regardless of the cancer subtypes, exhibited reproducible copy number variation (CNV) patterns, similar to those of the metastatic tumor of the same patient. Interestingly, different patients with the same lung cancer adenocarcinoma (ADC) shared similar CNV patterns in their CTCs. Even more interestingly, patients of smallcell lung cancer have CNV patterns distinctly different from those of ADC patients. Our finding suggests that CNVs at certain genomic loci are selected for the metastasis of cancer. The reproducibility of cancer-specific CNVs offers potential for CTC-based cancer diagnostics.cancer diagnostics | personalized therapy A s a genomic disease, cancer involves a series of changes in the genome, starting from primary tumors, via circulating tumor cells (CTCs), to metastases that cause the majority of mortalities (1-3). These genomic alterations include copy number variations (CNVs), single-nucleotide variations (SNVs), and insertions/deletions (INDELs). Regardless of the concentrated efforts in the past decades, the key driving genomic alterations responsible for metastases are still elusive (1).For noninvasive prognosis and diagnosis of cancer, it is desirable to monitor genomic alterations through the circulatory system. Genetic analyses of cell-free DNA fragments in peripheral blood have been reported (4-6) and recently extended to the whole-genome scale (7-9). However, it may be advantageous to analyze CTCs, as they represent intact functional cancer cells circulating in peripheral blood (10). Although previous studies have shown that CTC counting was able to predict progression and overall survival of cancer patients (11,12), genomic analyses of CTCs could provide more pertinent information for personalized therapy (13). However, it is difficult to probe the genomic changes in DNA obtainable from the small number of captured CTCs. To meet this challenge, a single-cell whole-genome amplification (WGA) method, multiple annealing and loopingbased amplification cycles (MALBAC) (14), has been developed to improve the amplification uniformity across the entire genome over previous methods (15,16), allowing precise determination of CNVs and detection of SNVs with a low false-positive rate in a single cell. Here, we present genomic analyses of CTCs from...

This study explores whether blood tumor mutational burden estimated by a next-generation sequencing gene panel is associated with clinical outcomes of patients with non–small cell lung cancer treated with anti–programmed cell death 1 and anti–programmed cell death ligand 1 agents.

Introduction: Programmed death receptor-1 (PD-1) inhibitors have shown efficacy in first-line treatment of NSCLC; however, evidence of PD-1 inhibitor as neoadjuvant treatment is limited. This is a phase 1b study to evaluate the safety and outcome of PD-1 inhibitor in neoadjuvant setting. Methods: Treatment-naive patients with resectable NSCLC (stage IA-IIIB) received two cycles of sintilimab (200 mg, intravenously, day 1 out of 22). Operation was performed between day 29 and 43. Positron emission tomographycomputed tomography scans were obtained at baseline and before the operation. The primary end point was safety. Efficacy end points included rate of major pathologic response (MPR) and objective response rate. Expression of programmed cell death ligand 1 was also evaluated (registration number: ChiCTR-OIC-17013726). Results: A total of 40 patients enrolled, all of whom received two doses of sintilimab and 37 underwent radical resection. A total of 21 patients (52.5%) experienced neoadjuvant treatment-related adverse events (TRAEs). Four patients (10.0%) experienced grade 3 or higher neoadjuvant TRAEs, and one patient had grade 5 TRAE. Eight patients achieved radiological partial response, resulting in an objective response rate of 20.0%. Among 37 patients, 15 (40.5%) achieved MPR, including six (16.2%) with a pathologic complete response in primary tumor and three (8.1%) in lymph nodes as well. Squamous cell NSCLC exhibited superior response compared with adenocarcinoma (MPR: 48.4% versus 0%). Decrease of maximum standardized uptake values after sintilimab treatment correlated with pathologic remission (p < 0.00001). Baseline programmed cell death ligand 1 expression of stromal cells instead of tumor cells was correlated with pathologic regression (p ¼ 0.0471).

Biomarkers such as programmed death receptor 1 ligand (PD-L1) expression, tumor mutational burden (TMB), and high microsatellite instability are potentially applicable to predict the efficacy of immune checkpoint blockade (ICB). However, several challenges such as defining the cut-off value, test platform uniformity, and low frequencies limit their broad clinical application. Here we identify comutations in the DNA damage response (DDR) pathways of homologous recombination repair and mismatch repair (HRR-MMR) or HRR and base excision repair (HRR-BER; defined as co-mut) that are associated with increased TMB and neoantigen load and increased levels of immune gene expression signatures. In four public clinical cohorts, co-mut patients presented a higher objective response rate and a longer progression-free survival or overall survival than co-mut patients. Overall, identification of DDR comutations in HRR-MMR or HRR-BER as predictors of response to ICB provides a potentially convenient approach for future clinical practice. Identification of comutations in specific DDR pathways as predictors of superior survival outcomes in response to immune checkpoint blockade provide a clinically convenient approach for estimation of tumor mutational burden and delivery of ICB therapy. .

Our results suggest that chemotherapy may reduce EGFR mutation frequency in patients with NSCLC, likely the result of a preferential response of subclones with EGFR mutations in tumors with heterogeneous tumor cell populations.

T-cell receptor (TCR)-based biomarkers might predict patient response to immune checkpoint blockade (ICB) but need further exploration and validation for that use. We sequenced complementarity-determining region 3 of TCRb chains isolated from PD-1 þ CD8 þ T cells to investigate its value for predicting the response to anti-programmed cell death 1 (PD-1)/PD-ligand 1 (PD-L1) therapy in patients with non-small cell lung cancer (NSCLC). Two independent patient cohorts (cohort A, n ¼ 25; cohort B, n ¼ 15) were used as discovery and validation sets, respectively. Pre-and post-ICB peripheral blood samples were collected. In cohort A, patients with high PD-1 þ CD8 þ TCR diversity before ICB treatment showed better response to ICB and progression-free survival (PFS) compared with patients with low diversity [6.4 months vs. 2.5 months, HR, 0.39; 95% confidence interval (CI), 0.17-0.94; P ¼ 0.021]. The results were validated in cohort B. Pre-ICB PD-1 þ CD8 þ TCR diversity achieved an optimal Youden's index of 0.81 (sensitivity ¼ 0.87 and specificity ¼ 0.94) for differentiating the ICB response in the merged dataset (cohort A plus cohort B). Patients with increased PD-1 þ CD8 þ TCR clonality after ICB treatment had longer PFS (7.3 months vs. 2.6 months, HR, 0.26; 95% CI, 0.08-0.86; P ¼ 0.002) than those with decreased clonality. Thus, TCR diversity and clonality in peripheral blood PD-1 þ CD8 þ T cells may serve as noninvasive predictors of patient response to ICB and survival outcomes in NSCLC.

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