Lipoplatin Formulation Review Article

Informing Patient Surveillance for the Growing Number of Survivors of Lung Cancer

Highlights from Recent Cancer Literature

The Center for Global Early Detection at MD Anderson has initiated two longitudinal early detection studies: LEAP (Lung Cancer Early Detection and Prevention, 2013-2019) for lung cancer screening and MERIT (Mammography Early Detection Risk Assessment and Imaging Technologies, 2017-ongoing) for breast cancer screening. Both cohorts enrolled subjects based on US standard-of-care guidelines at the time of enrollment for low-dose CT screening and mammography, respectively. The cohorts collected detailed health data from questionnaires, imaging data, and blood specimens at the time of screening. In addition to information on the screened-detected cancers, follow-up information was collected on any other types of cancers that are diagnosed after enrollment. Here, we evaluate the incidence of other cancers without available screening to assess the potential impact of multi-cancer early detection studies for these two types of screening populations. The two studies enrolled approximately 9,300 subjects (N = 2853 for LEAP; N = 6,400 for MERIT) with median follow up times of 2.99 years (IQR: 1.09-4.08) for LEAP and 2.05 years (IQR: 0.09-3.01) for MERIT. Currently, there are more than 800,000 aliquots of banked biospecimens from both cohorts. The incidence of lung cancer for the LEAP cohort undergoing low-dose CT screening was 0.91% per year. Cancers other than lung cancer were also diagnosed after enrollment including prostate, breast, bladder, head, and neck, colorectal, lymphoma, endocrine, gynecologic, and kidney cancers. Overall, the incidence of other cancers in LEAP was high for those cancers without available screening - 0.49% per year excluding breast, prostate, and colorectal cancers. The incidence of breast cancer for women in LEAP was lower than expected, 0.17% per year, likely a result of underscreening by mammography. For the MERIT cohort, the incidence of breast cancer was 0.89% per year. Cancers other than breast were diagnosed in MERIT after enrollment including gynecologic, melanoma, lung, colorectal, endocrine, bladder, and gastrointestinal cancers. The incidence of other cancers in MERIT was 0.55% per year, excluding colorectal cancer. We conclude that the incidence of cancers without a current screening modality in LEAP and MERIT is sufficiently high (0.49-0.55% per year) to justify the application of multi-cancer screening. Even for cancers with standard-of-care screening, a multi-cancer blood-based biomarker test could be useful given the possibility of underscreening, as we observed for breast cancer in the LEAP cohort. Citation Format: Jennifer Dennison, Ehsan Irajizad, Edwin Ostrin, Myrna Godoy, Olena Weaver, Jessica Leung, Samir Hanash. Application of multi-cancer early detection to lung and breast cancer screening populations. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P057.

Does a young woman living with a smoker or taking a job working in a smoky bar have a greater chance of developing breast cancer? Some scientists believe that such situations can indeed raise a woman’s risk of developing breast cancer before the age of 50. Because epidemiological and toxicological studies show that women’s breast tissue may be especially sensitive to exposure to carcinogens prior to first pregnancy, these researchers contend that public education should be directed at alerting adolescents and young women to the potential risk. However, not everyone in the international public health community agrees that the evidence to date supports a link between passive smoking and breast cancer, and some say that women are being alarmed unnecessarily. This disagreement has sparked debate that is sometimes heated. The stakes are high because breast cancer is the most common cancer in women in industrialized countries, according to the WHO. It is the leading cancer killer of nonsmoking women, and second only to lung cancer deaths among women who smoke. Among the researchers interviewed for this article who disagree that there is enough evidence to link secondhand smoke (SHS) with breast cancer, the majority call the evidence to date “suggestive but not sufficient,” as the Surgeon General’s 2006 report, The Health Consequences of Involuntary Exposure to Tobacco Smoke, put it. That characterization is based largely on the fact that the research considered when the Surgeon General’s report was being amassed did not clearly link even active smoking to breast cancer. Researchers in this camp do, however, stress that ongoing campaigns to prohibit smoking in public will protect the whole of society against the wide variety of ills proven to be caused by SHS. These include lung cancer, cardiovascular disease, and sudden infant death syndrome, among others. A smaller group contends that the question of whether or not SHS causes breast cancer is a political issue with the potential to compromise the scientific process. “A premature decision about causality could jeopardize the credibility of the entire review process and all of the other, established effects of secondhand smoke,” says Michael Thun, national vice president of epidemiology and surveillance research for the American Cancer Society. Adds Valerie Beral, director of the University of Oxford Cancer Research UK Epidemiology Unit, “To prematurely come to conclusions about the causation when there is a big division in the scientific community . . . is bad science.” Thun debated the subject in a series of public forums held in conjunction with scientific meetings. Taking the opposing view was Kenneth C. Johnson, a research scientist with the Public Health Agency of Canada, who was one of the first scientists to discern a potential link. During the debates, Johnson pointed out there are about the same number of studies linking breast cancer to passive smoking as there were linking lung cancer to SHS in 1986, when the Surgeon General concluded that passive smoking caused lung cancer. Johnson also says that more of the breast cancer studies are statistically significant, and that the estimated risk for breast cancer is higher.

Head and Neck Cancer Chemoprevention Gets a Shot in the Arm

Immunohistochemistry is important to the pathologist for accurate diagnosis of lung cancer. In recent studies, a rabbit polyclonal p40 (RPp40) antibody demonstrated equivalent staining versus anti-p63 in lung squamous cell carcinoma, and superior specificity because it stains a lesser percentage of lung adenocarcinoma. To develop an anti-p40 mouse monoclonal antibody (MMp40) for immunohistochemistry, and to evaluate its sensitivity and specificity in normal and neoplastic tissues, with emphasis on lung cancer. The MMp40 (BC28) antibody was developed and tested for specificity and sensitivity on normal (n = 34) and neoplastic tissues (n = 493). Staining of MMp40, p63, and RPp40 were directly compared in lung cancers, and MMp40 was evaluated in breast, bladder, skin, prostate, and head and neck cancers. Benign prostate glands and prostatic intraepithelial neoplasia were also tested in a direct comparison of MMp40 versus p63. The MMp40 provided equivalent staining versus RPp40 and p63 in lung squamous cell carcinoma, but stained a lesser percentage of lung adenocarcinoma than p63 did. The MMp40 staining was observed in a greater percentage of urothelial carcinomas, squamous and basal cell skin cancers, and head and neck cancers of squamous cell origin. No breast-infiltrating ductal carcinomas or prostatic adenocarcinomas were stained. The MMp40 expression in basal cells of prostate glands and prostatic intraepithelial neoplasia were almost identical to those of p63. The MMp40 (BC28) monoclonal antibody is a high-quality screening antibody for determining squamous cell carcinoma in lung cancers, skin cancers of squamous or basal cell origin, squamous cell head and neck cancers, and urothelial carcinomas.

Introduction: Cardiovascular disease (CVD) and cancer share a common risk factor: chronic toxic stress/allostatic load (AL). Our previous research found that a 1-point increase in AL is linked to a 25-30% higher risk of major cardiac events (MACE) in prostate cancer patients. Hypothesis: Higher AL is associated with increased MACE risk in patients with breast, lung, and colon cancer. Methods: Patients ≥18 years diagnosed for the first time with the mentioned 3 cancers of interest between 2010-2019 at a large, hybrid academic-community practice were included in this retrospective cohort study. AL was modeled as an ordinal measure (0-11; Table 1 ). Adjusted Fine-Gray Cox proportional hazard regressions estimated the impact of AL pre- and 60 days post- cancer diagnosis on 2-year MACE. Results: Demographic characteristics are summarized in Table 1. Two-year mace MACE occurred in 12.3%, 23.3%, and 9.7% of breast, lung, and colon cancer patients, respectively. Heart failure was the most common MACE, observed in 7.9%, 14.4%, and 4.8% of breast, lung, and colon cancer patients, respectively. Before cancer diagnosis, a 1-point increase in AL raised MACE risk by 11% (aHR=1.11, 95% CI 1.07-1.16) in breast cancer, 18% (aHR=1.18, 95% CI 1.11-1.25) in lung cancer, and 9% (aHR=1.09, 95% CI 1.01-1.18) in colon cancer. After cancer diagnosis, a 1-point increase in AL increased MACE risk by 10% (aHR=1.10, 95% CI 1.06-1.15) in breast cancer and 19% (aHR=1.19, 95% CI 1.12-1.25) in lung cancer, but was not statistically significant in colon cancer (aHR=1.07, 95% CI 0.99-1.16). Conclusion(s): Higher AL levels prior to breast, lung, and colon cancer diagnoses are associated with increased MACE risk. Thus, effective implementation of patient-centered communication considering stress levels, stressors, and coping mechanisms is necessary during cardiovascular screening for these cancer patients. Further prospective studies are needed.

Ras-related nuclear protein (Ran) is required for cancer cell survival in vitro and human cancer progression, but the molecular mechanisms are largely unknown. We investigated the effect of the v-myc myelocytomatosis viral oncogene homolog (Myc) on Ran expression by Western blot, chromatin immunoprecipitation, and luciferase reporter assays and the effects of Myc and Ran expression in cancer cells by soft-agar, cell adhesion, and invasion assays. The correlation between Myc and Ran and the association with patient survival were investigated in 14 independent patient cohorts (n = 2430) and analyzed with Spearman's rank correlation and Kaplan-Meier plots coupled with Wilcoxon-Gehan tests, respectively. All statistical tests were two-sided. Myc binds to the upstream sequence of Ran and transactivates Ran promoter activity. Overexpression of Myc upregulates Ran expression, whereas knockdown of Myc downregulates Ran expression. Myc or Ran overexpression in breast cancer cells is associated with cancer progression and metastasis. Knockdown of Ran reverses the effect induced by Myc overexpression in breast cancer cells. In clinical data, a positive association between Myc and Ran expression was revealed in 288 breast cancer and 102 lung cancer specimens. Moreover, Ran expression levels differentiate better or poorer survival in Myc overexpressing breast (χ2 = 24.1; relative risk [RR] = 9.1, 95% confidence interval [CI] = 3.3 to 24.7, P < .001) and lung (χ2 = 6.04; RR = 2.8, 95% CI = 1.2 to 6.3; P = .01) cancer cohorts. Our results suggest that Ran is required for and is a potential therapeutic target of Myc-driven cancer progression in both breast and lung cancers.

Surfactant protein D (SP-D) is an innate immune molecule that was originally discovered in the lungs as a part of pulmonary surfactant system. Later on, it became evident that SP-D has extensive tissue distribution that lent its credentials as a versatile innate immune molecule of mucosal system. In addition to its ability to protect against pathogens and allergens, and to modulate inflammatory reactions, SP-D has emerged as an immune surveillance molecule against cancer. SP-D can induce apoptosis in a variety of cancer cell lines and primary cancer cells derived from patients, including lung, pancreatic, prostate, ovarian and breast cancers. The apoptotic mechanisms including pathways, signaling and key mediators involved, have been delineated. The most striking feature of recent studies is the demonstration that a recombinant form of human SP-D (rfhSP-D) composed of homotrimeric C-type lectin domains can bring about these anti-tumor effects, raising the possibility of a therapeutic development. In addition to apoptosis induction, rfhSP-D can also interfere with epithelial-to-mesenchymal (EMT) transition in pancreatic cancer. In view of the above-mentioned in vitro studies, a recent bioinformatics analysis has examined if SP-D can serve as a potential prognostic marker for human lung cancer. It appears that compared to their normal tissue counterparts, there is a lower expression of SP-D in lung, gastric, and breast cancers, as opposed to ovarian cancer. In the lung cancer, the existence of SP-D is likely to be associated with a favourable prognosis.

BackgroundMitochondrial voltage-dependent anion channels (VDACs) play a key role in mitochondria-mediated apoptosis. Both in vivo and in vitro evidences indicate that VDACs are actively involved in tumor progression. Specifically, VDAC-1, one member of the VDAC family, was thought to be a potential anti-cancer therapeutic target. Our previous study demonstrated that the human gene VDAC1 (encoding the VDAC-1 isoform) was significantly up-regulated in lung tumor tissue compared with normal tissue. Also, we found a significant positive correlation between the gene expression of VDAC1 and histological grade in breast cancer. However, the prognostic power of VDAC1 and its associated genes in human cancers is largely unknown.MethodsWe systematically analyzed the expression pattern of VDAC1 and its interacting genes in breast, colon, liver, lung, pancreatic, and thyroid cancers. The genes differentially expressed between normal and tumor tissues in human carcinomas were identified.ResultsThe expression level of VDAC1 was uniformly up-regulated in tumor tissue compared with normal tissue in breast, colon, liver, lung, pancreatic, and thyroid cancers. Forty-four VDAC1 interacting genes were identified as being commonly differentially expressed between normal and tumor tissues in human carcinomas. We designated VDAC1 and the 44 dysregulated interacting genes as the VDAC1 associated gene signature (VAG). We demonstrate that the VAG signature is a robust prognostic biomarker to predict recurrence-free survival in breast, colon, and lung cancers, and is independent of standard clinical and pathological prognostic factors.ConclusionsVAG represents a promising prognostic biomarker in human cancers, which may enhance prediction accuracy in identifying patients at higher risk for recurrence. Future therapies aimed specifically at VDAC1 associated genes may lead to novel agents in the treatment of cancer.

Telomeres are located at the ends of chromosomes and are essential for chromosome stability and replication. They progressively get shorter with cell division, eventually resulting in cell proliferation arrest. The process is considered a barrier to tumor occurrence [1, 2]. Abnormally activated telomerase with constitutive telomerase reverse transcriptase (TERT) expression is a hallmark of almost all human tumors [3]. Some genomic alterations in the human TERT (hTERT) promoter are associated with activation of hTERT transcription in various cancer types [4]. The regulation of TERT expression can significantly affect tumor occurrence and progression. While lacking TATA and CAAT boxes, the hTERT promoter region contains an E-box which interacts with the transcription factor (TF) MYC, and a GC-box which is targeted by TF Sp1 [5]. The hTERT promoter also interacts with TFs as well as upstream stimulatory factors [6]. Furthermore, friend leukemia integration 1 (FLI1) specifically binds to novel transcription binding sites created by hTERT promoter mutations that frequently occur in tumors, thereby enhancing telomerase activity [7]. Thus, identification of other upstream regulators of hTERT could enrich our knowledge on the regulatory hTERT network involved in tumor biology. To understand the molecular mechanisms underlying hTERT promoter activity, we screened, with the hTERT promoter sequence, a protein microarray made of a candidate subset of TFs selected from a larger microarray of 667 TFs [7, 8]. Two TFs – transcription factor binding to IGHM enhancer 3 (TFE3) and zinc finger protein 556 (ZNF556) – exhibited particularly strong binding to the hTERT promoter (Figure 1A). Since TFE3 is known to be associated with the occurrence and progression of several tumors [9], we focused our analyses on this molecule, leaving ZNF556 for future studies. TFE3 is a regulator of hTERT. (A) Left panel: Screening of the binding of the hTERT promoter sequence to a protein microarray made of 96 TFs; a typical result is shown; pos. – positive control; neg. – negative control; blank – empty spots. Right panel: Quantification of the results; mean intensities, and the related standard deviations (SD) of the signals are given next to results of individual TFs. (B) The binding site prediction was confirmed in ChIP experiments with anti-TFE3 antibody on chromatin isolated from NCI-H1299 cells. As a negative control, rabbit IgGs were used instead of the anti-TFE3 antibody. Next to the predicted binding sites at -170 bp and +29 bp, an unrelated DNA at position -5329 bp was used as a control. The degree of enrichment of the respective DNA segment was quantified by qPCR. (C) hTERT promoter activity is measured by a luciferase reporter assay in vector pGL3. HEK293T cells were subjected to knockdowns with an siRNA targeting TFE3 (siTFE3) and a control siRNA with scrambled, unspecific sequence. The relative fluorescence is shown that was produced by the luciferase activity. (D) siRNA-mediated knockdown of TFE3 down-regulates hTERT and CCND1 expression in NCI-H1299. The effect of the TFE3 knockdown and the consequential reduction of hTERT and CCND1 transcript levels are shown. (E) The effect is also shown at the protein level by Western blot, comparing results obtained with an siRNA construct with scrambled sequence and a molecule targeting TFE3 (siTFE3). (F) Cell cycle analysis with NCI-H1299 cells subjected to TFE3 knockdown or treated with a scrambled siRNA sequence. Cell percentages are shown. (G) Expression of TFE3 and CCND1 in lung cancer tissues in comparison to their levels in healthy control samples. The data were obtained from the Oncomine expression database. TFE3 and CCND1 were found up-regulated in tumors in comparison to the respective healthy tissues (normal). * P < 0.05; ** P < 0.01; *** P < 0.001. Abbreviations: TFE3, transcription factor binding to IGHM enhancer 3; hTERT, human telomerase reverse transcriptase; CCND1, cyclin D1; bp, base pair; siRNA, small interfering RNA; IgG, immunoglobulin G; qPCR, quantitative polymerase chain reaction; ChIP, chromatin immunoprecipitation In silico prediction of binding sites in the hTERT promoter region indicated two TFE3 binding sites (Supplementary Figure S1A, B), one at -170 bp upstream of the transcription start site (TSS) on the positive strand, and the other one at +29 bp downstream on the negative strand Supplementary Figure S2A). We performed chromatin immunoprecipitation with anti-TFE3 antibody to confirm TFE3 binding. The core binding sequence was significantly enriched compared to the immunoglobulin G (IgG) control; a non-promoter region acting as negative control produced an even weaker signal (Figure 1B and Supplementary Figure S2B). To verify the role of TFE3 in hTERT activation, we measured the promoter activity with a luciferase reporter assay in HEK293T cells. After knocking down TFE3 (Supplementary Figure S2C), luciferase activity was decreased by about 10% (Figure 1C), indicating that TFE3 positively regulates the hTERT promoter activity by direct interaction. The relatively small effect of TFE3 knockdown is not surprising since several TFs have binding sites in the hTERT promoter (Supplementary Figure S2A). Nevertheless, there is a substantial contribution of TFE3 to the overall regulation of hTERT transcription. To explore the effect of TFE3 on hTERT expression, we measured hTERT transcript levels after TFE3 knockdown in the lung cancer cell line (NCI-H1299) and pancreatic cancer cell line (MiaPaCa-2). In NCI-H1299, TFE3 mRNA and protein levels were reduced significantly (Figure 1D-E). The effect was even more pronounced in MiaPaCa-2 cell line (Supplementary Figure S2D-E). Concomitantly to TFE3 knockdown, hTERT mRNA levels decreased by 20% in NCI-H1299 (Figure 1D) and dropped even more drastically in MiaPaCa-2 (Supplementary Figure S2D). In both cell lines, the hTERT protein level was also reduced (Supplementary Figure S3A). The difference between the cells could partly be the result of different knockdown efficacy. Additionally, MiaPaCa-2 has already a relatively lower endogenous hTERT expression. To confirm that TFE3 binds specifically to the promoter region and exerts its effect on hTERT, we simulated site-directed mutagenesis in silico. A change of one highly conserved base of the TFE3 binding motif led to the loss of binding (data not shown). These results imply that TFE3 positively regulates the expression of hTERT. Besides analyzing the changes to hTERT, we looked at the expression of cell cycle-associated marker cyclin D1 (CCND1), since several regulators of hTERT activity have been reported to influence the cell cycle. Knockdown of TFE3 affected its binding partner hTERT and reduced CCND1 expression (Figure 1D-E and Supplementary Figure S2D-E), suggesting that TFE3 is involved in cell cycle regulation. Knockdown of TFE3 also elevated cyclin-dependent kinase inhibitor 1B (p27) protein levels, an upstream regulator of CCND1, indicating that p27 is involved in stopping or slowing down of the cell division. There was no change in tumor protein p53 levels (Supplementary Figure S3A). To rule out that this effect was due to mutations in the hTERT promoter, we performed a dual luciferase reporter assay with wildtype hTERT promoter and a version with hotspot mutation G250A. There was no change in promoter activity, emphasizing that the effect was in fact due to TFE3 binding (Supplementary Figure S3B). For confirmation of the functional consequence indicated by CCND1, we performed cell cycle analyses after TFE3 knockdown. In NCI-H1299, the cell percentage in the G0/G1 phase increased by 8%, decreased by 6% in the S phase and did not change significantly in the G2/M phase (Figure 1F). MiaPaCa-2 cell percentages increased by 9% in the G0/G1 phase, decreased by 5% in the S phase, and 3% in the G2/M phase (Supplementary Figure S2F) inferring that TFE3 moderately promotes cell cycle progression. In order to show that TFE3 promotes cancer development also through other hTERT related functions, we performed apoptosis and ROS assays. Apoptosis was increased upon TFE3 knockdown and no difference in ROS activity in both the cell lines was observed (Supplementary Figure S3C-D). To confirm that the relationship of TFE3 and CCND1 could also be observed in human tumor tissues rather than merely in cell lines, the transcript profiles of the Oncomine data repository were used. Both TFE3 and CCND1 were significantly up-regulated not only in lung and pancreatic cancer tissues (Figure 1G and Supplementary Figure S2G), but also in kidney, breast, colorectal and gastric tumors compared to respective healthy control samples (Supplementary Figure S4) indicating a common feature across tumors. Due to the low expression level of hTERT, TFE3 and hTERT showed no or only weak correlation in pancreatic and lung cancers. TFE3 and CCND1 were weakly correlated in 4/6 datasets (data not shown). Given the known interactions and large number of predicted TF binding sites in hTERT, it is likely that several TFs orchestrate the regulation of hTERT, repressing or activating the gene in a concerted manner, which could be further affected by genetic and epigenetic factors. Our study shows that TFE3 may act as a diagnostic marker in solid-pseudo papillary neoplasms and granular cell tumors. Also, TFE3-associated gene fusion and translocation is relatively common in some tumors and hTERT promoter rearrangements were detected in renal cell carcinoma subtypes. However, the effect of TFE3 on the hTERT promoter activity had not been reported before. TFE3 regulates hTERT activity positively and promotes cell cycle progression. As a functional partner of the E2F3 transcription factor, TFE3 is essential to DNA replication, which is another critical factor related to cell cycle control [10]. In conclusion, TFE3 directly triggers hTERT expression and is a newly identified part of the overall complex regulation of telomere biology, which is critical to tumor survival. Not applicable Not applicable The authors declare no conflict of interest. The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. We thank Dr. Jing Yang (German Cancer Research Centre, DKFZ, Heidelberg) for her technical support in bioinformatic analysis and Cuncai Guo (University Hospital Heidelberg, Heidelberg) for technical support in Western blot experiments. Open access funding enabled and organized by Projekt DEAL. BPM, JDH, ORB designed the study. BPM, CYZ, NS, LB; KH conducted the experiments and collected the data. BPM, ORB analyzed the data and interpreted the results. BPM, CYZ, JDH, ORB wrote the manuscript. All authors read and approved the final manuscript. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

BackgroundObservational studies indicate that periodontal disease may increase the risk of colorectal, lung, and pancreatic cancers. Using a 2-sample Mendelian randomization (MR) analysis, we assessed whether a genetic predisposition index for periodontal disease was associated with colorectal, lung, or pancreatic cancer risks.MethodsOur primary instrument included single nucleotide polymorphisms with strong genome-wide association study evidence for associations with chronic, aggressive, and/or severe periodontal disease (rs729876, rs1537415, rs2738058, rs12461706, rs16870060, rs2521634, rs3826782, and rs7762544). We used summary-level genetic data for colorectal cancer (n = 58 131 cases; Genetics and Epidemiology of Colorectal Cancer Consortium, Colon Cancer Family Registry, and Colorectal Transdisciplinary Study), lung cancer (n = 18 082 cases; International Lung Cancer Consortium), and pancreatic cancer (n = 9254 cases; Pancreatic Cancer Consortia). Four MR approaches were employed for this analysis: random-effects inverse‐variance weighted (primary analyses), Mendelian Randomization-Pleiotropy RESidual Sum and Outlier, simple median, and weighted median. We conducted secondary analyses to determine if associations varied by cancer subtype (colorectal cancer location, lung cancer histology), sex (colorectal and pancreatic cancers), or smoking history (lung and pancreatic cancer). All statistical tests were 2-sided.ResultsThe genetic predisposition index for chronic or aggressive periodontitis was statistically significantly associated with a 3% increased risk of colorectal cancer (per unit increase in genetic index of periodontal disease; P = .03), 3% increased risk of colon cancer (P = .02), 4% increased risk of proximal colon cancer (P = .01), and 3% increased risk of colorectal cancer among females (P = .04); however, it was not statistically significantly associated with the risk of lung cancer or pancreatic cancer, overall or within most subgroups.ConclusionsGenetic predisposition to periodontitis may be associated with colorectal cancer risk. Further research should determine whether increased periodontitis prevention and increased cancer surveillance of patients with periodontitis is warranted.

PCN101 - Economic Burdens of the Top 10 Cancers During 2003-2012 in Taiwan

> GEM models that accurately model human cancer at both the molecular and phenotypic levels are new tools that are available for experimental therapeutic studies The proposal of new therapeutic strategies for cancer patients has been greatly facilitated by our deepening knowledge of the molecular

Objective. Different radiation therapy (RT) strategies, e.g. conventional fractionation RT (CFRT), hypofractionation RT (HFRT), stereotactic body RT (SBRT), adaptive RT, and re-irradiation are often used to treat head and neck (HN) cancers. Combining and/or comparing these strategies requires calculating biological effective dose (BED). The purpose of this study is to develop a practical process to estimate organ-specific radiobiologic model parameters that may be used for BED calculations in individualized RT planning for HN cancers. Approach. Clinical dose constraint data for CFRT, HFRT and SBRT for 5 organs at risk (OARs) namely spinal cord, brainstem, brachial plexus, optic pathway, and esophagus obtained from literature were analyzed. These clinical data correspond to a particular endpoint. The linear-quadratic (LQ) and linear-quadratic-linear (LQ-L) models were used to fit these clinical data and extract relevant model parameters (alpha/beta ratio, gamma/alpha, d T and BED) from the iso-effective curve. The dose constraints in terms of equivalent physical dose in 2 Gy-fraction (EQD2) were calculated using the obtained parameters. Main results. The LQ-L and LQ models fitted clinical data well from the CFRT to SBRT with the LQ-L representing a better fit for most of the OARs. The alpha/beta values for LQ-L (LQ) were found to be 2.72 (2.11) Gy, 0.55 (0.30) Gy, 2.82 (2.90) Gy, 6.57 (3.86) Gy, 5.38 (4.71) Gy, and the dose constraint EQD2 were 55.91 (54.90) Gy, 57.35 (56.79) Gy, 57.54 (56.35) Gy, 60.13 (59.72) Gy and 65.66 (64.50) Gy for spinal cord, optic pathway, brainstem, brachial plexus, and esophagus, respectively. Additional two LQ-L parameters d T were 5.24 Gy, 5.09 Gy, 7.00 Gy, 5.23 Gy, and 6.16 Gy, and gamma/alpha were 7.91, 34.02, 8.67, 5.62 and 4.95.Significance. A practical process was developed to extract organ-specific radiobiological model parameters from clinical data. The obtained parameters can be used for biologically based radiation planning such as calculating dose constraints of different fractionation regimens.