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Cancer has many faces − 5 counterintuitive ways scientists are approaching cancer research to improve treatment and prevention
From math to evolutionary game theory, looking at cancer through different lenses can offer further insights on how to approach treatment resistance, metastasis…
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How researchers conceptualize a disease informs how they treat it. Cancer is often described as uncontrollable cell growth triggered by genetic damage. But cancer can also be seen from angles that emphasize mathematics, evolutionary game theory and physics, among others.
Molecular biology has brought significant advances in making it possible to live with cancer as a chronic illness rather than a fatal disease. Alternative frameworks, however, can offer scientists additional insights on how to prevent tumors from spreading throughout the body and becoming resistant to treatment.
Here are a few unconventional lenses through which researchers are viewing cancer with fresh eyes, drawn from The Conversation’s archives.
1. Evolution and natural selection of cancer
The body is far from a wonderland for cells. Each individual cell competes against trillions of others for finite space and nutrients. If they’re able to cooperate in an orderly enough fashion, sharing resources and dividing labor, the collective functions effectively. Cancer cells, however, cheat the system: They hog resources, take up as much space as possible and refuse to die.
In this way, cancer can be thought of as an evolutionary disease – these are cells that have developed the genetic mutations to outcompete their neighbors, and subsequent cell generations inherit this survival advantage. Cancer cells benefit at the expense of the collective until the entire organism collapses.
Oncologist Monika Joshi and pathologists Joshua Warrick and David DeGraff believe that understanding evolution is key to understanding cancer. Screening programs are effective, for example, because removing a nascent tumor is easier than treating one that has evolved the ability to spread. Cancer cells likewise become resistant to treatments because they’re pushed to further evolve to survive.
Some researchers are applying the principles of evolutionary game theory to reduce treatment resistance and optimize therapies for children.
“The fight against cancer is a fight against evolution, the fundamental process that has driven life on Earth since time immemorial,” they wrote. “This is not an easy fight, but medicine has made tremendous progress.”
2. Fluid mechanics of cancer
As much as cancer is a disease that respects no boundaries, tumor cells are still shaped by their environment. Unlike healthy cells that take the hint when their presence isn’t wanted, however, tumor cells not only survive but thrive in stressful conditions. Isolated cancer cells able to adapt to harsh settings are the ones that establish metastatic colonies and become resistant to treatment.
While researchers have focused on how biochemical signals direct cells to move from one location to another, a cell’s physical environment also affects where it migrates. Mechanical engineer Yizeng Li found that a cell’s “solid” and “fluid” surroundings influence its movement.
Cancer cells encounter varying degrees of fluid viscosity, or thickness, as they travel through the body. Li and her team found that breast cancer cells counterintuitively move faster in high viscosity environments by changing their structure. This meant that fluid viscosity serves as a mechanobiological cue for cancer cells to metastasize.
“Cancer patients usually don’t die from the original source of the tumor but from its spread to other parts of the body,” Li wrote. “Understanding how fluid viscosity affects the movement of tumor cells could help researchers figure out ways to better treat and detect cancer before it metastasizes.”
3. Inflammation link to cardiovascular disease
Apart from being leading causes of death around the world, cardiovascular disease and cancer may not initially seem to have much in common. The many risk factors they share, however – like poor diet, smoking and chronic stress – coalesce with chronic inflammation: persistent, low-grade activation of the immune system can damage cells in ways that encourage either disease to develop.
For biomedical engineer Bryan Smith, the developmental parallels between these diseases signal they could be treated at the same time.
Drugs can be repurposed to target diseases for which they weren’t originally designed. Certain drugs, for example, can direct immune cells called macrophages to consume both cancer cells and the cellular debris that contribute to cardiovascular plaques.
“As basic science discovers other molecular parallels between these diseases, patients will be the beneficiaries of better therapies that can treat both,” wrote Smith.
4. Mathematics of cancer
In certain contexts, math has unique strengths in describing the natural world. For instance, epigenetics – where and when genes are turned on or off – plays as much a role in cancer progression as direct changes to the genetic code. Epigenetic changes can alter healthy cells to the point of losing their normal form and function. But the randomness of these changes makes it difficult to tease out pathological from normal genetic activity.
A mathematical concept called stochasticity – or how the randomness of the steps of a process influences how predictable its outcome will be – lends a logical framework to the epigenetic changes contributing to cancer, clarifying when healthy cells rapidly develop into tumor cells.
Stochasticity is commonly used to study stock market behavior and epidemic disease spread, and researchers quantify it by examining the degree of uncertainty, or entropy, of a particular outcome. Identifying high entropy areas in the genome could offer another approach to cancer detection and drug design.
Cancer geneticist Andrew Feinberg has been using entropy to quantitatively describe the epigenetics of cancer. He and his colleagues found that high entropy regions of the genome in the skin become even more entropic with sun damage, increasing the chance of developing cancer. This offers a potential explanation for why cancer risk significantly increases with age.
“Epigenetic entropy shows that you can’t fully understand cancer without mathematics,” Feinberg wrote. “Biology is catching up with other hard sciences in incorporating mathematical methods with biological experimentation.”
5. A public health issue
Cancer is a disease that develops in an individual, but its socially derived causes and societal-wide effects are hardly limited to a single person.
Take the case of lung cancer. It is stigmatized as a disease brought on by poor lifestyle choices – a consequence of a personal decision to use tobacco products. But as thoracic oncologist Estelamari Rodriguez noted, the face of lung cancer has changed.
“Over the past 15 years, more women, never-smokers and younger people are being diagnosed with lung cancer,” she wrote. While lung cancer rates have significantly decreased for men, they have substantially risen for women around the world. Despite being the leading cause of cancer death among women, screening rates remain low compared with other cancers.
More broadly, cancer symptoms are often unrecognized or misdiagnosed, not only for women but also for many marginalized populations, including people of color, transgender patients and the uninsured.
These disparities are due in part to biases in medical education and clinical research that fail to prepare clinicians to care for the diversity of patients they’ll encounter. Tenuous access to preventive care and disproportionate exposure to carcinogens among certain populations compound these inequities.
The purview of cancer goes far beyond a single discipline. It takes a village of researchers, policymakers and patient advocates to achieve effective and accessible cancer care for all.
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Uncategorized
February Employment Situation
By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…
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By Paul Gomme and Peter Rupert
The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.
Temporary help services employment continues a steep decline after a sharp post-pandemic rise.
Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.
The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.
The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.
Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.
As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.
Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.
The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.
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Mortgage rates fall as labor market normalizes
Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.
The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250
Below is an explanation of how we got here with the labor market, which all started during COVID-19.
1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.
2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.
Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.
3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too
Total employment data
4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels.
From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.
Here are the jobs that were created and lost in the previous month:
In this jobs report, the unemployment rate for education levels looks like this:
- Less than a high school diploma: 6.1%
- High school graduate and no college: 4.2%
- Some college or associate degree: 3.1%
- Bachelor’s degree or higher: 2.2%
Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.
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Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month
Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month
Last month we though that the January…
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Last month we though that the January jobs report was the "most ridiculous in recent history" but, boy, were we wrong because this morning the Biden department of goalseeked propaganda (aka BLS) published the February jobs report, and holy crap was that something else. Even Goebbels would blush.
What happened? Let's take a closer look.
On the surface, it was (almost) another blockbuster jobs report, certainly one which nobody expected, or rather just one bank out of 76 expected. Starting at the top, the BLS reported that in February the US unexpectedly added 275K jobs, with just one research analyst (from Dai-Ichi Research) expecting a higher number.
Some context: after last month's record 4-sigma beat, today's print was "only" 3 sigma higher than estimates. Needless to say, two multiple sigma beats in a row used to only happen in the USSR... and now in the US, apparently.
Before we go any further, a quick note on what last month we said was "the most ridiculous jobs report in recent history": it appears the BLS read our comments and decided to stop beclowing itself. It did that by slashing last month's ridiculous print by over a third, and revising what was originally reported as a massive 353K beat to just 229K, a 124K revision, which was the biggest one-month negative revision in two years!
Of course, that does not mean that this month's jobs print won't be revised lower: it will be, and not just that month but every other month until the November election because that's the only tool left in the Biden admin's box: pretend the economic and jobs are strong, then revise them sharply lower the next month, something we pointed out first last summer and which has not failed to disappoint once.
In the past month the Biden department of goalseeking stuff higher before revising it lower, has revised the following data sharply lower:
— zerohedge (@zerohedge) August 30, 2023
- Jobs
- JOLTS
- New Home sales
- Housing Starts and Permits
- Industrial Production
- PCE and core PCE
To be fair, not every aspect of the jobs report was stellar (after all, the BLS had to give it some vague credibility). Take the unemployment rate, after flatlining between 3.4% and 3.8% for two years - and thus denying expectations from Sahm's Rule that a recession may have already started - in February the unemployment rate unexpectedly jumped to 3.9%, the highest since February 2022 (with Black unemployment spiking by 0.3% to 5.6%, an indicator which the Biden admin will quickly slam as widespread economic racism or something).
And then there were average hourly earnings, which after surging 0.6% MoM in January (since revised to 0.5%) and spooking markets that wage growth is so hot, the Fed will have no choice but to delay cuts, in February the number tumbled to just 0.1%, the lowest in two years...
... for one simple reason: last month's average wage surge had nothing to do with actual wages, and everything to do with the BLS estimate of hours worked (which is the denominator in the average wage calculation) which last month tumbled to just 34.1 (we were led to believe) the lowest since the covid pandemic...
... but has since been revised higher while the February print rose even more, to 34.3, hence why the latest average wage data was once again a product not of wages going up, but of how long Americans worked in any weekly period, in this case higher from 34.1 to 34.3, an increase which has a major impact on the average calculation.
While the above data points were examples of some latent weakness in the latest report, perhaps meant to give it a sheen of veracity, it was everything else in the report that was a problem starting with the BLS's latest choice of seasonal adjustments (after last month's wholesale revision), which have gone from merely laughable to full clownshow, as the following comparison between the monthly change in BLS and ADP payrolls shows. The trend is clear: the Biden admin numbers are now clearly rising even as the impartial ADP (which directly logs employment numbers at the company level and is far more accurate), shows an accelerating slowdown.
But it's more than just the Biden admin hanging its "success" on seasonal adjustments: when one digs deeper inside the jobs report, all sorts of ugly things emerge... such as the growing unprecedented divergence between the Establishment (payrolls) survey and much more accurate Household (actual employment) survey. To wit, while in January the BLS claims 275K payrolls were added, the Household survey found that the number of actually employed workers dropped for the third straight month (and 4 in the past 5), this time by 184K (from 161.152K to 160.968K).
This means that while the Payrolls series hits new all time highs every month since December 2020 (when according to the BLS the US had its last month of payrolls losses), the level of Employment has not budged in the past year. Worse, as shown in the chart below, such a gaping divergence has opened between the two series in the past 4 years, that the number of Employed workers would need to soar by 9 million (!) to catch up to what Payrolls claims is the employment situation.
There's more: shifting from a quantitative to a qualitative assessment, reveals just how ugly the composition of "new jobs" has been. Consider this: the BLS reports that in February 2024, the US had 132.9 million full-time jobs and 27.9 million part-time jobs. Well, that's great... until you look back one year and find that in February 2023 the US had 133.2 million full-time jobs, or more than it does one year later! And yes, all the job growth since then has been in part-time jobs, which have increased by 921K since February 2023 (from 27.020 million to 27.941 million).
Here is a summary of the labor composition in the past year: all the new jobs have been part-time jobs!
But wait there's even more, because now that the primary season is over and we enter the heart of election season and political talking points will be thrown around left and right, especially in the context of the immigration crisis created intentionally by the Biden administration which is hoping to import millions of new Democratic voters (maybe the US can hold the presidential election in Honduras or Guatemala, after all it is their citizens that will be illegally casting the key votes in November), what we find is that in February, the number of native-born workers tumbled again, sliding by a massive 560K to just 129.807 million. Add to this the December data, and we get a near-record 2.4 million plunge in native-born workers in just the past 3 months (only the covid crash was worse)!
The offset? A record 1.2 million foreign-born (read immigrants, both legal and illegal but mostly illegal) workers added in February!
Said otherwise, not only has all job creation in the past 6 years has been exclusively for foreign-born workers...
... but there has been zero job-creation for native born workers since June 2018!
This is a huge issue - especially at a time of an illegal alien flood at the southwest border...
... and is about to become a huge political scandal, because once the inevitable recession finally hits, there will be millions of furious unemployed Americans demanding a more accurate explanation for what happened - i.e., the illegal immigration floodgates that were opened by the Biden admin.
Which is also why Biden's handlers will do everything in their power to insure there is no official recession before November... and why after the election is over, all economic hell will finally break loose. Until then, however, expect the jobs numbers to get even more ridiculous.
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