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We consider a multi-type branching process model for the initiation of colorectal cancer, which progresses through a complex sequence of driver mutations. The model incorporates the relative fitness advantages conferred by driver mutations, which leads us to consider non-dividing sub-populations, and the effects of neutral and advantageous mutations. We analyze large-time limits to approximate the population sizes of sub-clones founded by neutral or advantageous mutations, and use the results to compute the waiting time distributions for the incidence of novel mutations in colorectal cancer initiation. Analytic waiting time distributions, including the distribution of waiting time to malignancy, are in good agreement with results from Monte Carlo simulations of the model. The approach presented here can be extended to other multi-type branching process models where population growth rates of consecutive types are non-decreasing.

Transformation to aggressive disease histologies generates formidable clinical challenges across cancers, but biological insights remain few. We modeled the genetic heterogeneity of chronic lymphocytic leukemia (CLL) through multiplexed in vivo CRISPR-Cas9 B-cell editing of recurrent CLL loss-of-function drivers in mice and recapitulated the process of transformation from indolent CLL into large cell lymphoma [i.e., Richter syndrome (RS)]. Evolutionary trajectories of 64 mice carrying diverse combinatorial gene assortments revealed coselection of mutations in Trp53, Mga, and Chd2 and the dual impact of clonal Mga/Chd2 mutations on E2F/MYC and interferon signaling dysregulation. Comparative human and murine RS analyses demonstrated tonic PI3K signaling as a key feature of transformed disease, with constitutive activation of the AKT and S6 kinases, downmodulation of the PTEN phosphatase, and convergent activation of MYC/PI3K transcriptional programs underlying enhanced sensitivity to MYC/mTOR/PI3K inhibition. This robust experimental system presents a unique framework to study lymphoid biology and therapy.Significance:Mouse models reflective of the genetic complexity and heterogeneity of human tumors remain few, including those able to recapitulate transformation to aggressive disease histologies. Herein, we model CLL transformation into RS through multiplexed in vivo gene editing, providing key insight into the pathophysiology and therapeutic vulnerabilities of transformed disease.This article is highlighted in the In This Issue feature, p. 101

Transformation to aggressive disease histologies generates formidable clinical challenges across cancers, but biological insights remain few. We modeled the genetic heterogeneity of chronic lymphocytic leukemia (CLL) through multiplexed in vivo CRISPR-Cas9 B-cell editing of recurrent CLL loss-of-function drivers in mice and recapitulated the process of transformation from indolent CLL into large cell lymphoma [i.e., Richter syndrome (RS)]. Evolutionary trajectories of 64 mice carrying diverse combinatorial gene assortments revealed coselection of mutations in Trp53, Mga, and Chd2 and the dual impact of clonal Mga/Chd2 mutations on E2F/MYC and interferon signaling dysregulation. Comparative human and murine RS analyses demonstrated tonic PI3K signaling as a key feature of transformed disease, with constitutive activation of the AKT and S6 kinases, downmodulation of the PTEN phosphatase, and convergent activation of MYC/PI3K transcriptional programs underlying enhanced sensitivity to MYC/mTOR/PI3K inhibition. This robust experimental system presents a unique framework to study lymphoid biology and therapy.Significance:Mouse models reflective of the genetic complexity and heterogeneity of human tumors remain few, including those able to recapitulate transformation to aggressive disease histologies. Herein, we model CLL transformation into RS through multiplexed in vivo gene editing, providing key insight into the pathophysiology and therapeutic vulnerabilities of transformed disease.This article is highlighted in the In This Issue feature, p. 101

Supplementary file contains a PDF version of supplementary figures S1-S7 and associated figure legends.

Supplementary file contains all supplementary tables S1-S16 in Excel format in the order in which they appear in the text.

The questions of how healthy colonic crypts maintain their size, and how homeostasis is disrupted by driver mutations, are central to understanding colorectal tumorigenesis. We propose a three-type stochastic branching process, which accounts for stem, transit-amplifying (TA) and fully differentiated (FD) cells, to model the dynamics of cell populations residing in colonic crypts. Our model is simple in its formulation, allowing us to easily estimate all but one of the model parameters from the literature. Fitting the single remaining parameter, we find that model results agree well with data from healthy human colonic crypts, capturing the considerable variance in population sizes observed experimentally. Importantly, our model predicts a steady state population in healthy colonic crypts for relevant parameter values. We show thatAPCandKRASmutations, the most significant early alterations leading to colorectal cancer, result in increased steady-state populations in mutated crypts, in agreement with experimental results. Finally, our model predicts a simple condition for unbounded growth of cells in a crypt, corresponding to colorectal malignancy. This is predicted to occur when the division rate of TA cells exceeds their differentiation rate, with implications for therapeutic cancer prevention strategies.

Objective: Polycystic ovary syndrome (PCOS) is associated with altered lipid profile and increased small, dense LDL particles (sdLDL). Considering that paraoxonase 1 (PON1) is an anti-oxidative enzyme located on high-density lipoprotein (HDL) particles, the aim of this study was to investigate the connection between oxidative stress (OS) and PON1 activity with lipoprotein subclasses in PCOS depending on obesity. Methods: In 115 PCOS patients lipoprotein subclasses distributions were determined by gradient gel electrophoresis. OS status was assessed by total oxidative status (TOS), advanced oxidation protein products (AOPP), malondialdehyde (MDA), prooxidant-Antioxidant balance (PAB), total antioxidant status (TAS) and superoxide dismutase (SOD) and PON1 activity. Results: Overweight/obese PCOS patients (n=55) had increased OS compared to normal weight patients (n=60). In addition, overweight/obese group had lower HDL size and higher proportion of HDL 3a subclasses (P

BACKGROUND Neuroendocrine tumors of appendix (ANETs) known as carcinoids, are rare endocrine neoplasms originated from enterochromaffin cells of gastrointestinal tract. ANETs are the third most frequent (16.7%) gastrointestinal neuroendocrine tumors, with the incidence of 0.08-0.2 cases/100000 during one year. Incidental ANETs occur in 0.2%-0.7% of emergency surgical resections because of suspected appendicitis which is usually the first manifestation of ANET. Although there are a lot of papers about application of somatostatin receptor scintigraphy in gastrointestinal neuroendocrine tumors, there are very rare sporadic cases described about ANETs particularly. AIM To establish the role of somatostatin receptor scintigraphy (SRS) in the management of patients with neuroendocrine tumors of appendix (ANET). METHODS The total of 35 patients was investigated, 23 females and 12 males, average age (43.7 ± 17.3 years). All patients had histological diagnosis of ANET (34 carcinoids of appendix and one tubular carcinoid). Majority of tumors have been found incidentally during surgery of: Acute appendicitis (n = 15), perforated appendicitis (n = 2), ileus (n = 3), hysterectomy (n = 3), ruptured ovarian cyst (n = 2), caecal volvulus (n = 1), while 9 patients had diagnosis of appendiceal tumor before the surgery. Seventeen patients had tumor grade (G) G1, 12 G2 and 6 G3. The right hemicolectomy was performed in 13, while the rest of the patients had appendectomy only. SRS was done early (2 h) and late (24 h) after i.v. application of 740 MBq technetium-99m ethylenediamine-N, N'-diacetic acid Hydrazinonicotinyl-Tyr3-Octreotide (technetium-99m-Tektrotyd, Polatom, Poland). SRS was performed for restaging in all the patients after surgery. RESULTS There were 12 true positive (TP), 19 true negative, 3 false positive and 1 false negative SRS result. Sensitivity of the method was 92.31%, specificity was 86.36%, positive predictive value was 80.00%, negative predictive value was 95.00% and accuracy 88.57%. Receiver operating characteristics analysis showed that SRS scintigraphy is a good test for detection TP cases [area under the curve of 0.850, 95% confidence interval (CI): 0.710-0.990, P < 001]. Single photon emission computed tomography contributed diagnosis in 7 TP findings. In 10 patients Krenning score was 4 and in 2 was 3. In 8 patients SRS significantly changed the management of the patients (in two surgery was repeated, in 4 somatostatin analogues and in two peptide receptor radionuclide therapy). Median progression-free survival in SRS positive patients was 52 months (95%CI: 39.7-117.3 mo) while in SRS negative patients it was 60 months (95%CI: 42.8-77.1 mo), without statistically significant difference between the two groups (P = 0.434). CONCLUSION In conclusion, our results confirmed the value of SRS in the follow-up of the patients with ANET after surgery, if recurrences or metastases are suspected.

Uncovering and quantifying the laws of the evolutionary dynamics of cancer, in particular in the context of specific genetic lesions and in individual patients, has the potential to revolutionize precision oncology. Recent technological advances in the study of human cancer have increased access to in vivo human data and have thereby facilitated the confirmation or refutation of existing theoretical models. In this Perspective, we discuss recent work at the intersection of quantitative mathematical models of cancer evolution and patient data that provides insights into different stages of tumor evolution, including premalignant and malignant progression and response to therapy. Bozic and Wu discuss how quantitative mathematical models elucidate the various stages of tumor evolution, from premalignancy to malignant progression, and the response to therapy.

Background A vestibular schwannoma (VS) is a relatively rare, benign tumour of the eighth cranial nerve, often involving alterations to the gene NF2. Previous mathematical models of schwannoma incidence have not attempted to account for alterations in specific genes, and could not distinguish between nonsense mutations and loss of heterozygosity (LOH). Methods Here, we present a mechanistic approach to modelling initiation and malignant transformation in schwannoma. Each parameter is associated with a specific gene or mechanism operative in Schwann cells, and can be determined by combining incidence data with empirical frequencies of pathogenic variants and LOH. Results This results in new estimates for the base-pair mutation rate u = 4.48 × 10−10 and the rate of LOH = 2.03 × 10−6/yr in Schwann cells. In addition to new parameter estimates, we extend the approach to estimate the risk of both spontaneous and radiation-induced malignant transformation. Discussion We conclude that radiotherapy is likely to have a negligible excess risk of malignancy for sporadic VS, with a possible exception of rapidly growing tumours.

BackgroundChildhood maltreatment (CM) and exposure to community violence (ETV) are correlated with physical/mental health and psychosocial problems. Typically, CM and ETV are examined separately, by subtypes within category, or collapsed across both into one category of adversity. Consequently, research is limited in identifying subgroups of individuals with different amounts of exposure to both CM and ETV. Accordingly, we lack sufficient understanding of the extent to which problems associated with CM and ETV vary based on the amount (i.e. dose) of exposure to both of these experiences.MethodsWe used 20 samples (28,300 individuals) to estimate person-centered profiles of CM and ETV occurrence and co-occurrence within each sample. An individual data multilevel meta-analytic framework was used to determine the average effect size across samples for different profiles and conditional probability correlations within sociodemographic, neighborhood, health, mental health, and psychosocial domains.ResultsThe profile characterized by high levels of CM and high levels of ETV correlated with stressful life events, depression and anxiety symptoms, and general indicators of externalizing behaviors. CM predominant profiles were associated with mental health diagnoses and treatment. ETV predominant profiles associated with risk-taking/violent behavior and neighborhood-level disadvantage. However, nuance based on the dose of CM or ETV was evident.ConclusionsIt is important to identify subgroups based on the amount of exposure to CM and ETV. These subgroups have differential relationships with correlates across domains. Greater delineation and description of the lived experience will allow for more precision in addressing the burden of childhood adversity.

How the genomic features of a patient’s cancer relate to individual disease kinetics remains poorly understood. Here we used the indolent growth dynamics of chronic lymphocytic leukaemia (CLL) to analyse the growth rates and corresponding genomic patterns of leukaemia cells from 107 patients with CLL, spanning decades-long disease courses. We found that CLL commonly demonstrates not only exponential expansion but also logistic growth, which is sigmoidal and reaches a certain steady-state level. Each growth pattern was associated with marked differences in genetic composition, the pace of disease progression and the extent of clonal evolution. In a subset of patients, whose serial samples underwent next-generation sequencing, we found that dynamic changes in the disease course of CLL were shaped by the genetic events that were already present in the early slow-growing stages. Finally, by analysing the growth rates of subclones compared with their parental clones, we quantified the growth advantage conferred by putative CLL drivers in vivo. Analysis of growth dynamics in a dataset from 107 patients with chronic lymphocytic leukaemia (CLL) reveals both exponential and logistic patterns of growth, which are associated with differences in genetic attributes and clinical outcomes.

Summary Background: Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant cancer syndrome characterized by the occurrence of primary hyperparathyroidism (PHPT), pituitary adenoma (PA) and pancreatic neuroendocrine tumor (pNET). Whether the underlying mutations in MEN1 gene predict clinical presentation of affected heterozygotes or not, is still a matter of a debate. Methods: Clinical and genetic analysis of 90 consecutive MEN1 patients was performed in a retrospective, single – center study. Results: MEN1 mutation was found in 67 (74.4%) patients belonging to 31 different families. Twenty nine different heteozygous mutations were found, including 6 novel point mutations (W220G, 941delG, 1088del7, 1184insA, 1473del10, 1602del17) and one large deletion of exon 8. Truncating mutations predicted development of pNETs (OR=5.8, 95% CI 1.7 – 19.7%) and PHPT (OR=4.3, 95% CI 1.5 – 12.4%). Conclusions: Large number of novel mutations among MEN1 patients confirmed previously reported data. PNETs and PHPT were more frequent in patients with truncating mutations.

Endocrine system plays a major role in both permissive and regulatory activities in order to adequately respond to physical stress of exercise. But level and direction of activation depend on many factors and are not easily interpreted.We tested a group of male professional athletes (21 water polo players and 15 wrestlers), together with 20 sedentary controls matched by age. All participants took a continuous progressive exercise stress test on a treadmill until exhaustion and plateau of oxygen consumption (VOCortisol levels significantly increased in both groups, but the response between S and MAX was more pronounced in controls (p=0.036). The athletes had significantly higher levels of cortisol in all points in test, except during R (p=0.118), when their cortisol levels gradually started to decline. Significant increase in total testosterone was in great deal a consequence of increase in SHBG level (p0.01 for both). Consequently, calculated free testosterone significantly decreased during test (p=0.008), and the drop was more pronounced in athletes. This was in concordance with significant correlation between SHBG and cortisol level demonstrated in athletes, but not in controls.It seems that high intensity endurance exercise favors catabolic response, but the level of response highly depends on a previous level of training.Endokrini sistem ima i permisivnu i regulatornu ulogu kako bi se adekvatno odgovorilo na fizički stress prouzrokovan vežbanjem. Ali nivo i smer aktivacije zavise od mnogih faktora i nisu jednostavni za interpretaciju.Testirali smo grupu muških profesionalnih sportista (21 vaterpolista i 15 rvača), i 20 sedentarnih kontrola upa renih prema godinama. Sproveden je ergospirome trijski test do iscrpljenosti i platoa potrošnje kiseonika (VONivo kortizola je značajno porastao u obe grupe, ali je odgovor između S i MAX bio naglašeniji kod kontrola (p=0,036). Sportisti su imali značajno više vrednosti kortizola u svim tačkama testa, izuzev tokom R (p=0,118), s obzirom da su njihove vrednosti kortizola počele da opadaju. Značajan porast vrednosti ukupnog testosterona je u velikoj meri bio posledica porasta nivoa SHBG (p0,01 za oba). Posledično, izračunate vrednosti slobodnog testosterona su značajno opadale tokom testa (p=0,008), a pad je bio izraženiji kod sportista. Ovaj rezultat je u skladu sa demonstriranom značajnom korelacijom između SHBG i korti zola kod sportista, ali ne i kod kontrola.Naši rezultati ukazuju da trening izdržljivosti visokog intenziteta favorizuje katabolički odgovor, ali nivo odgovora značajno zavisi od nivoa utreniranosti.

Measuring the selective fitness advantages provided by driver mutations has the potential to facilitate a precise quantitative understanding of cancer evolution. However, accurately measuring the selective advantage of driver mutations has remained a challenge in the field. Early studies reported small selective advantages of drivers, on the order of 1%, whereas newer studies report much larger selective advantages, as high as 1,200%. In this article, we argue that the calculated selective advantages of cancer drivers are dependent on the underlying mathematical model and stage of cancer evolution and that comparisons of numerical values of selective advantage without regard for the underlying model and stage can lead to spurious conclusions.

To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need a reliable estimate of their rate of transfer between bacterial cells. However, accurate estimates of plasmid transfer have remained elusive due to biological and experimental complexity. Current methods to measure transfer rate can be confounded by many factors. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. Inspired by the classic fluctuation analysis of Luria and Delbrück, we develop a novel approach, the Luria-Delbrück method (‘LDM’), for estimating plasmid transfer rate. Our new approach embraces the stochasticity of conjugation departing from the current deterministic population dynamic methods. In addition, the LDM overcomes obstacles of traditional methods by not being affected by different growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude.Significance StatementConjugative plasmids play significant roles in the ecology and evolution of microbial communities. Notably, antibiotic resistance genes are often encoded on conjugative plasmids. Thus, conjugation—the transfer of a plasmid copy from one cell to another—is a common way for antibiotic resistance to spread between important clinical pathogens. For both public health modeling and a basic understanding of microbial population biology, accurate estimates of this fundamental rate are of great consequence. We show that widely used methods can lead to biased estimates, deviating from true values by several orders of magnitude. Therefore, we developed a new approach, inspired by the classic fluctuation analysis of Luria and Delbrück, for accurately assessing the rate of plasmid conjugation under a variety of conditions.

Despite the effectiveness of many cancer therapies in reducing tumor burden for significant amounts of time in a subset of patients, primary and acquired resistance to treatment remain one of the biggest challenges in the effort to cure cancer. Successful management, or prevention, of resistance requires deciphering the mechanisms by which it arises, and in particular whether it stems from pre-existing cell populations or arises de novo during therapy. Using evolutionary principles and mathematical techniques together with patient data, we aim to develop a precise mathematical understanding of the dynamics of response and resistance to various cancer therapies, including targeted therapies and immunotherapy. Our work shows that therapies that maximize the killing rate of cancer cells may not be optimal, and that instead the parameters determining the fraction of resistant cells and their growth rate have a larger effect on the long-term control of cancer. Citation Format: Ivana Bozic. Dynamics of response and resistance to cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr IA020.

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. We apply our methodology to reconstruct the individual evolutionary histories of chronic lymphocytic leukemia patients. Fitting our model to longitudinal patient data reveals strengths and weaknesses of using an exponential model of cancer growth with constant mutation rate to estimate parameters of cancer evolution.

The Federal Drug Administration (FDA) approved the first Chimeric Antigen Receptor T-cell (CAR T-cell) therapies for the treatment of several blood cancers in 2017, and efforts are underway to broaden CAR T technology to address other cancer types. Standard treatment protocols incorporate a preconditioning regimen of lymphodepleting chemotherapy prior to CAR T-cell infusion. However, the connection between preconditioning regimens and patient outcomes is still not fully understood. Optimizing patient preconditioning plans and reducing the CAR T-cell dose necessary for achieving remission could make therapy safer. In this paper, we test treatment regimens consisting of sequential administration of chemotherapy and CAR T-cell therapy on a system of differential equations that models the tumor-immune interaction. We use numerical simulations of treatment plans from within the scope of current medical practice to assess the effect of preconditioning plans on the success of CAR T-cell therapy. Model results affirm clinical observations that preconditioning can be crucial for some patients, not just to reduce side effects, but to even achieve remission at all. We demonstrate that preconditioning plans using the same CAR T-cell dose and the same total concentration of chemotherapy can lead to different patient outcomes due to different delivery schedules. Results from sensitivity analysis of the model parameters suggest that making small improvements in the effectiveness of CAR T-cells in attacking cancer cells, rather than targeting the recruitment and longevity of CAR T-cells, will significantly reduce the minimum dose required for successful treatment. Our modeling framework represents a starting point for evaluating the efficacy of patient preconditioning in the context of CAR T-cell therapy.

Quantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53, and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of incomplete mutational genotypes on the way to colorectal cancer. We parametrize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported incidence of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined by the combined effect of the rates at which driver genes are mutated and the fitness effects they provide. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.

BACKGROUND: Drug-induced Liver Injury (DILI) is an important cause of acute liver failure cases in the United States, and remains a common cause of withdrawal of drugs in both preclinical and clinical phases. METHODS: A structured search of bibliographic databases - Web of Science Core Collection, Scopus and Medline for peer-reviewed articles on models of DILI was performed. The reference lists of relevant studies was prepared and a citation search for the included studies was carried out. In addition, the characteristics of screened studies were described. RESULTS: One hundred and six articles about the existing knowledge of appropriate models to study DILI in vitro and in vivo with special focus on hepatic cell models, variations of 3D co-cultures, animal models, databases and predictive modeling and translational biomarkers developed to understand the mechanisms and pathophysiology of DILI are described. CONCLUSION: Besides descriptions of current applications of existing modeling systems, associated advantages and limitations of each modeling system and future directions for research development are discussed as well.

Treatment of chronic lymphocytic leukemia (CLL) has shifted from chemo-immunotherapy to targeted agents. To define the evolutionary dynamics induced by targeted therapy in CLL, we perform serial exome and transcriptome sequencing for 61 ibrutinib-treated CLLs. Here, we report clonal shifts (change >0.1 in clonal cancer cell fraction, Q, In a subset of patients with chronic lymphocytic leukemia (CLL) treated with targeted agents, such as ibrutinib, drug resistant subclones emerge. Here, the authors report on transcriptional changes in CLL patients treated with ibrutinib and identify early clonal shifts associated with evolution of resistant clones.

Targeted therapies, immunotherapies, and improved chemotherapies are being developed to reduce the suffering and mortality that come from human cancer. Although these approaches, and in particular combinations of them, are expected to succeed eventually to a large degree, they all suffer one obstacle: Populations of replicating cells move away—typically in a high-dimensional space—from any opposing selection pressure they encounter. They evolve resistance. It is possible, however, to develop a precise mathematical understanding of the problem and to design treatment strategies that prevent resistance if possible or manage resistance otherwise. In this article, we present the fundamental equations that characterize the evolution of resistance. We provide formulas for the probability that resistant cells exist at the start of therapy, for the average number and sizes of resistant clones, and for the probability of successful combination treatment. We also demonstrate that developing new therapies that only maximize the killing rate of cancer cells may not be optimal, and that instead the parameters determining the fraction of resistant cells and their growth rate have a larger effect on the long-term control of cancer. These mathematical tools inform the search process for optimal therapies that aim to cure cancer.

France is one of the largest economies of the world and one of the most influential countries of the EU, and its centuries-old friendship with Serbia and a strategic position in the Western Balkans and the complementarity of economies represent a good basis for the development of bilateral economic relations. However, despite the great potential for cooperation, mutual cooperation results to date are not at a high level. One of the reasons may well be just the language barrier and the lack of knowledge of French market culture. The aim of this paper is to present forms of economic cooperation between Serbia and France, to emphasize the importance of the knowledge of French language and intercultural competence as a prerequisite for cooperation, at least in the initial marketing terms. In this paper, we will give a brief historical overview of the French economic relations, and by employing a complementary analysis we will present the mutual trade between the two countries, and we will as well point out the importance of knowing the French language and French culture to the employees who have plans for successful cooperation with French partners.