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Background Monte Carlo simulation is considered as the most accurate method for dose calculation in radiotherapy. PRIMO is a Monte-Carlo program with a user-friendly graphical interface. Material and method A VitalBeam with 6MV and 6MV flattening filter free (FFF), equipped with the 120 Millennium multileaf collimator was simulated by PRIMO. We adjusted initial energy, energy full width at half maximum (FWHM), focal spot FWHM, and beam divergence to match the measurements. The water tank and ion-chamber were used in the measurement. Percentage depth dose (PDD) and off axis ratio (OAR) were evaluated with gamma passing rates (GPRs) implemented in PRIMO. PDDs were matched at different widths of standard square fields. OARs were matched at five depths. Transmission factor and dose leaf gap (DLG) were simulated. DLG was measured by electronic portal imaging device using a sweeping gap method. Result For the criterion of 2%/2 mm, 1%/2 mm and 1%/1 mm, the GPRs of 6MV PDD were 99.33–100%, 99–100%, and 99–100%, respectively; the GPRs of 6MV FFF PDD were 99.33–100%, 98.99–99.66%, and 97.64–98.99%, respectively; the GPRs of 6MV OAR were 96.4–100%, 90.99–100%, and 85.12–98.62%, respectively; the GPRs of 6MV FFF OAR were 95.15–100%, 89.32–100%, and 87.02–99.74%, respectively. The calculated DLG matched well with the measurement (6MV: 1.36 mm vs. 1.41 mm; 6MV FFF: 1.07 mm vs. 1.03 mm, simulation vs measurement). The transmission factors were similar (6MV: 1.25% vs. 1.32%; 6MV FFF: 0.8% vs. 1.12%, simulation vs measurement). Conclusion The calculated PDD, OAR, DLG and transmission factor were all in good agreement with measurements. PRIMO is an independent (with respect to analytical dose calculation algorithm) and accurate Monte Carlo tool.

Purpose: There are very little data available comparing outcomes of intensity-modulated proton therapy (IMPT) to intensity-modulated radiation therapy (IMRT) in patients with locally advanced NSCLC (LA-NSCLC). Methods: Seventy-nine consecutively treated patients with LA-NSCLC underwent definitive IMPT (n = 33 [42%]) or IMRT (n = 46 [58%]) from 2016 to 2018 at our institution. Survival rates were calculated using the Kaplan-Meier method and compared with the log-rank test. Acute and subacute toxicities were graded based on Common Terminology Criteria for Adverse Events, version 4.03. Results: Median follow-up was 10.5 months (range, 1-27) for all surviving patients. Most were stage III (80%), received median radiation therapy (RT) dose of 60 Gy (range, 45-72), and had concurrent chemotherapy (65%). At baseline, the IMPT cohort was older (76 vs 69 years, P

Gastric cancer (GC), a leading cause of cancer-related death, is a heterogeneous disease. We aim to describe clinically relevant molecular classifications of GC that incorporate heterogeneity and provide useful clinical information. We combined different gene expression datasets and filtered a 7-gene signature related to the extracellular matrix (ECM), which also exhibited significant prognostic value in GC patients. Interestingly, putative CCCTC-binding factor (CTCF) regulatory elements were identified within the promoters of these ECM-related genes and were confirmed by chromatin immunoprecipitation sequencing (ChIP-Seq). CTCF binding sites also overlapped with histone activation markers, indicating direct regulation. In addition, CTCF was also correlated with the Wnt signaling pathway. A comparison of human GC cell lines with high or low expression of ECM-related genes revealed different levels of tumor aggressiveness, suggesting the cancer development-promoting functions of ECM-related genes. Furthermore, CTCF regulated COL1A1 and COLA31 expression in vitro. Silencing CTCF or COL1A1/COL1A3 markedly inhibited cell growth and migration in the metastatic GC cell line BGC823. Collectively, this ECM-related 7-gene signature provides a novel insight for survival prediction among GC patients. The zinc finger protein CTCF regulates ECM-related genes, thereby promoting GC cell growth and migration.

Hepatocellular carcinoma is one of the most common malignant tumors worldwide and the fourth leading cause of cancer-related deaths. The prognosis of hepatocellular carcinoma patients is extremely poor due to the occult onset and high metastasis of hepatocellular carcinoma. Therefore, biomarkers with high specificity and sensitivity are of great importance in early screening, diagnosis prognosis, and treatment of hepatocellular carcinoma patients. Exosomes are tiny vesicles secreted by various types of cells, which can serve as mediators of intercellular communication to regulate the tumor microenvironment, and play a key role in the occurrence, development, prognosis, monitor and treatment of hepatocellular carcinoma. As microRNA deliverer, exosomes are involved in multiple life activities by regulating target genes of recipient cells such as proliferation, invasion, metastasis and apoptosis of cancer cells. In this review, we summarized the composition, active mechanism and function of exosomal microRNAs in hepatocellular carcinoma, and elaborated on their potential application value of early diagnosis and treatment in hepatocellular carcinoma.

MicroRNAs (miRNAs or miRs) are non-coding small RNAs that target specific messenger RNAs to inhibit protein translation. miR-200a and miR-141 function as tumor suppressors by targeting STAT4. These two miRNAs belong to the same family, and their expression is often decreased in various cancer types, but are located on different chromosomes of the human genome. The present study showed that the expression levels of miR-141 and miR-200a in serum and cells of liver cancer are significantly downregulated. The expression levels of miR-141 and miR-200a are closely associated with clinicopathological features of liver cancer, especially metastasis and invasion. It is first reported that STAT4 is the new common target gene of miR-141 and miR-200a. In the present study, miR-141 and miR-200a were confirmed to inhibit the expression of E-cadherin and vimentin synergistically during epithelial-mesenchymal transition to regulate the proliferation, migration and invasion of liver cancer cells by targeting STAT4. Simultaneous overexpression of miR-200a and miR-141 resulted in stronger effects compared with each miRNA alone. In addition, overexpression of STAT4 significantly reversed the tumor suppressive roles of miR-200a and miR-141 in liver cancer cells. These findings enrich the tumor suppressor mechanisms of the miR-200 family, and may also provide new experimental and theoretical basis for the use of miRNAs for early diagnosis, prognosis and thorough treatment of liver cancer.

Hepatocellular carcinoma (HCC) is one of the most common clinically malignant tumors of the digestive system. It ranks the sixth most common malignant tumor in the world and ranks fourth among cancer-related death worldwide. At present, early diagnosis and prognosis monitoring of hepatocellular carcinoma mainly use alpha-fetoprotein combined with ultrasonography, which leads to clinical frequently missed diagnosis or even misdiagnosis. Therefore, seeking specific diagnostic and monitoring molecules of hepatocellular carcinoma are still hot topics in contemporary medical practice. MicroRNA is an endogenous non-coding small RNA that regulates the expression of the target molecule and participates in various biological processes in vivo. The miR-200 family, the most common celebrity family of microRNAs, is commonly lower expression in a variety of cancers and is closely associated with tumorigenesis and outcome, especially hepatocellular carcinoma. This review mainly discusses the expression changes, specific molecular mechanisms, biological functions and clinical values of miR-200 family in hepatocellular carcinoma. Moreover, we highlighted utilization of miR-200 family as molecular biomarkers for early diagnosis, prognostic monitoring and appropriate therapy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common malignant tumor in the digestive tract with limited therapeutic choices. Intercellular communication among cancer cells and their microenvironment is crucial to disease progression. Exosomes are extracellular vesicles secreted by multiple types of cells into the extracellular space, which contain a variety of active components of secretory cells, including lipids, proteins, RNA and DNA. This vesicle structure involves in the exchange of materials and information between cells and plays an important role in the development of many diseases. Studies have shown that exosomes participate in the communication between HCC cells and non-HCC cells and regulate the occurrence and development of hepatocellular carcinoma. Therefore, exosomes may be specific biomarkers for early diagnosis and metastasis of HCC, which are also potential targets for the treatment of HCC. This review summarizes the characteristic, types and biological functions of exosomes and discusses their research progress and application prospects in the diagnosis and treatment of HCC.

Purpose/Objective(s) We previously identified changes of immune cells in the cervical cancer microenvironment following concurrent chemoradiotherapy (CCRT) at single cell resolution. However, changes of other cells in the tumor microenvironment are unknown; thus, we further investigated CCRT-induced landscape alteration of all cells in the tumor microenvironment of locally advanced cervical cancer (LACC) using single-cell RNA sequencing. Materials/Methods We performed single-cell RNA sequencing of 5 paired of tumor biopsies before and during CCRT in LACC patients and identified the subsets of epithelial cells, cancer-associated fibroblasts, immune cells, and endothelial cells and their alterations following CCRT. We also used immunostaining to validate our findings. Results Seven clusters of epithelial cells, 2 clusters of mCAF and 7 clusters of vCAF, 7 clusters of myeloid cells, 10 clusters of T cells and 2 clusters of NK cells, and 3 clusters of endothelial cells were identified in cervical cancer. Epithelial cells, mCAF and myeloid cells dramatic changed following CCRT. The proportion of a highly proliferate cluster of epithelial cells was decreased induced by CCRT, while a pre-malignant cluster of epithelial cells was predominant during CCRT. CCRT induced the transition of mCAF from one subset to another. For T cells, CCL5+CD8+ T cells, exhausted CD8+ T cells, and proliferate T cells were predominant before CCRT, but not during CCRT; cytotoxic CD8+ T cells were mainly existed in the tumor environment during CCRT. Conclusion Our work reveals the landscape alteration of tumor microenvironment induced by CCRT in LACC patients at single-cell resolution.

Purpose/Objective(s) Microbiome in cervical cancer tissue remains largely unknown, although cervicovaginal microbiome was investigated in various studies. We investigated the microbiome in cancer tissues and vagina, and its impact on tumor response after concurrent chemoradiotherapy (CCRT) in locally advanced cervical cancer (LACC) patients. Materials/Methods We prospectively enrolled 63 LACC patients who received CCRT and collected their tumor biopsies and vaginal swabs before and during CCRT. 16S rRNA gene sequencing was used to evaluated the microbiome in samples. Tumor response was evaluated based on RECIST 1.1 guidelines at one month after CCRT. Results Complete response (CR) was found in 50 (79%) patients, while partial response (PR) or stable disease (SD) was shown in 13 (21%) patients after CCRT. Patients with CR showed higher beta-diversity (P = 0.021) but not alpha-diversity (P > 0.05) in pretreatment tumor tissues than patients with PR/SD. Different microbiome composition in tumor tissues and vaginal swabs was observed between patients with CR and PR/SD at the two time points. KEGG showed significantly increased metabolic pathways, such as amino acid metabolism, energy metabolism, nucleotide metabolism, and lipid metabolism, in patients with CR than with PR/SD. Interestingly, alpha-diversity was significantly higher in cervical cancer tissues than in vaginal swabs during CCRT (P 0.05). Conclusion Our work reveals the microbiome in tumor microenvironment and vagina and its correction with tumor response after CCRT in LACC patients. Further study was warranted to explore which microbe regulates tumor response by which metabolic pathway. Author Disclosure C. Liu: None. A. Li: None. C. Wang: None. W. Zou: None. J. Yu: None. L. Zhang: None. X. Zhang: None. J. Yue: None.

Purpose: There is an emerging interest of applying magnetic resonance imaging (MRI) to radiotherapy (RT) due to its superior soft tissue contrast for accurate target delineation as well as functional information for evaluating treatment response. MRI-based RT planning has great potential to enable dose escalation to tumors while reducing toxicities to surrounding normal tissues in RT treatments of nasopharyngeal carcinoma (NPC). Our study aims to generate synthetic CT from T2-weighted MRI using a deep learning algorithm. Methods: Thirty-three NPC patients were retrospectively selected for this study with local IRB's approval. All patients underwent clinical CT simulation and 1.5T MRI within the same week in our hospital. Prior to CT/MRI image registration, we had to normalize two different modalities to a similar intensity scale using the histogram matching method. Then CT and T2 weighted MRI were rigidly and deformably registered using intensity-based registration toolbox elastix (version 4.9). A U-net deep learning algorithm with 23 convolutional layers was developed to generate synthetic CT (sCT) using 23 NPC patients' images as the training set. The rest 10 NPC patients were used as the test set (~1/3 of all datasets). Mean absolute error (MAE) and mean error (ME) were calculated to evaluate HU differences between true CT and sCT in bone, soft tissue and overall region. Results: The proposed U-net algorithm was able to create sCT based on T2-weighted MRI in NPC patients, which took 7 s per patient on average. Compared to true CT, MAE of sCT in all tested patients was 97 ± 13 Hounsfield Unit (HU) in soft tissue, 131 ± 24 HU in overall region, and 357 ± 44 HU in bone, respectively. ME was −48 ± 10 HU in soft tissue, −6 ± 13 HU in overall region, and 247 ± 44 HU in bone, respectively. The majority soft tissue and bone region was reconstructed accurately except the interface between soft tissue and bone and some delicate structures in nasal cavity, where the inaccuracy was induced by imperfect deformable registration. One patient example was shown with almost no difference in dose distribution using true CT vs. sCT in the PTV regions in the sinus area with fine bone structures. Conclusion: Our study indicates that it is feasible to generate high quality sCT images based on T2-weighted MRI using the deep learning algorithm in patients with nasopharyngeal carcinoma, which may have great clinical potential for MRI-only treatment planning in the future.

Purpose We propose linear energy transfer (LET)-guided robust optimization in intensity modulated proton therapy for head and neck cancer. This method simultaneously considers LET and physical dose distributions of tumors and organs at risk (OARs) with uncertainties. Methods and Materials Fourteen patients with head and neck cancer were included in this retrospective study. Cord, brain stem, brain, and oral cavity were considered. Two algorithms, voxel-wise worst-case robust optimization and LET-guided robust optimization (LETRO), were used to generate intensity modulated proton therapy plans for each patient. The latter method directly optimized LET distributions rather than indirectly as in previous methods. LET–volume histograms (LETVHs) were generated, and high LET was redistributed from nearby OARs to tumors in a user-defined way via LET–volume constraints. Dose–volume histogram indices, such as clinical target volume (CTV) D98% and D2%-D98%, cord Dmax, brain stem Dmax, brain Dmax, and oral cavity Dmean, were calculated. Plan robustness was quantified using the worst-case analysis method. LETVH indices analogous to dose–volume histogram indices were used to characterize LET distributions. The Wilcoxon signed rank test was performed to measure statistical significance. Results In the nominal scenario, LETRO provided higher LET distributions in the CTV (unit: keV/μm; CTV LET98%: 1.18 vs 1.08, LETRO vs RO, P = .0031) while preserving comparable physical dose and plan robustness. LETRO achieved significantly reduced LET distributions in the cord, brain stem, and oral cavity compared with RO (cord LETmax: 7.20 vs 8.20, P = .0010; brain stem LETmax: 10.95 vs 12.05, P = .0007; oral cavity LETmean: 2.11 vs 3.12, P = .0052) and had comparable physical dose and plan robustness in all OARs. In the worst-case scenario, LETRO achieved significantly higher LETmean in the CTV, reduced LETmax in the brain, and was comparable to other LETVH indices (CTV LETmean: 3.26 vs 3.35, P = .0012; brain LETmax: 24.80 vs 22.00, P = .0016). Conclusions LETRO robustly optimized LET and physical dose distributions simultaneously. It redistributed high LET from OARs to targets with slightly modified physical dose and plan robustness.

Purpose To investigate how spot size and spacing affect plan quality, robustness, and interplay effects of robustly optimized intensity modulated proton therapy (IMPT) for lung cancer. Methods and Materials Two robustly optimized IMPT plans were created for 10 lung cancer patients: first by a large-spot machine with in-air energy-dependent large spot size at isocenter (σ: 6-15 mm) and spacing (1.3 σ), and second by a small-spot machine with in-air energy-dependent small spot size (σ: 2-6 mm) and spacing (5 mm). Both plans were generated by optimizing radiation dose to internal target volume on averaged 4-dimensional computed tomography scans using an in-house–developed IMPT planning system. The dose–volume histograms band method was used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effects with randomized starting phases for each field per fraction. Patient anatomy voxels were mapped phase-to-phase via deformable image registration, and doses were scored using in-house–developed software. Dose–volume histogram indices, including internal target volume dose coverage, homogeneity, and organs at risk (OARs) sparing, were compared using the Wilcoxon signed-rank test. Results Compared with the large-spot machine, the small-spot machine resulted in significantly lower heart and esophagus mean doses, with comparable target dose coverage, homogeneity, and protection of other OARs. Plan robustness was comparable for targets and most OARs. With interplay effects considered, significantly lower heart and esophagus mean doses with comparable target dose coverage and homogeneity were observed using smaller spots. Conclusions Robust optimization with a small spot-machine significantly improves heart and esophagus sparing, with comparable plan robustness and interplay effects compared with robust optimization with a large-spot machine. A small-spot machine uses a larger number of spots to cover the same tumors compared with a large-spot machine, which gives the planning system more freedom to compensate for the higher sensitivity to uncertainties and interplay effects for lung cancer treatments.

159 Background: Intensity-modulated proton therapy (IMPT) with small spot size has the potential to reduce dose to normal tissues but also introduces new confounding factors such as setup uncertainty, range uncertainty, and interplay effects due to breathing motion. We investigated plan quality and robustness of IMPT with small spot size for distal esophageal adenocarcinoma (DEA). Methods: 19 patients with DEA treated by IMPT were retrospectively evaluated. Spot sizes ranged from 2 to 6mm, with spot spacing of 5mm. All plans were generated using a commercial treatment planning system. In-house-developed dose-evaluation software modeled time-dependent spot delivery to incorporate interplay effects. Dose-volume-histogram (DVH) indices were used to evaluate plan quality and robustness was evaluated using the DVH band method. Results: For plan quality, median values of clinical target volume D95% and D5%-D95% (normalized to the prescribed doses), total lung mean dose, heart mean dose, and cord Dmax were 1.014, 0.035, 3.82Gy[RBE], 7.73Gy[RBE], 39.16Gy[RBE], respectively. For plan robustness, median band widths of the aforementioned DVH indices were 0.018, 0.048, 0.60Gy[RBE], 4.17Gy[RBE], and 2.36Gy[RBE], respectively. For interplay effects, median values of the aforementioned DVH indices were 0.99, 0.061, 4.07Gy[RBE], 7.87Gy[RBE], and 39.66Gy[RBE], respectively. Seven patients underwent esophagectomy after neoadjuvant chemoradiation, and five, three, and one of them achieved downstaging, near complete response, and pathologic complete response, respectively; R0 resection was achieved in all cases. For all patients, acute side effects were mostly limited to grades 1-2 only. The only grade 3 adverse events were related to feeding tube placement (8 patients); there were no RT-induced pneumonitis or other lung-related toxicities. Conclusions: IMPT plans with small spot size for DEA have good target dose coverage, homogeneity and normal tissue protection. Treatment plans are also robust to uncertainties and interplay effects. Early clinical results demonstrate low acute toxicity and encouraging clinical and pathologic response.